Documents published in 2020 : Scipedia

User Equilibrium and System Optimum with Incomplete Information In Traffic Congestion
S. Liu, M. Masoud, Q. Zhang

Collection of open conferences in research transport (2020). Vol. 2020, 86

Abstract
By providing more information about traffic network, such as more feasible paths via intelligent navigation systems (INS), users in the network may change their choices of the path from a source to a destination. This paper investigates a traffic congestion model with incomplete information, in which different users have different information about the network. We introduce the notions of user equilibrium of incomplete information (UEII) and system optimum of incomplete information (SOII). Then, we prove a theorem about the effect of the change of traffic amount on each couple paths in SOII for the model. Finally, based on this theorem and a property of UEII, we reveal a relationship between UEII and SOII on the cost function.
Abstract
By providing more information about traffic network, such as more feasible paths via intelligent navigation systems (INS), users in the network may change their choices of [...]
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OpenStreetMap: an opportunity for Citizen Science
A. Sarretta, M. Minghini, M. Napolitano, A. Kotsev, P. Mooney

Collection of open conferences in research transport (2020). Vol. 2020, 85

Abstract
OpenStreetMap (OSM, https://www.openstreetmap.org) is currently the largest, richest, most complete and most up-to-date open geospatial database as well as the most participated crowdsourced geographic information project in the world. While it was initially started (in 2004) with an exclusive focus on road network, it now covers any real-world feature that is verifiable on the ground. The project currently counts more than 5.5 million registered users, with an average of about 5,000 users contributing to the map on a daily basis [1]."br" Currently, the relation between OSM and science is mostly focused on studying various aspects of OSM such as data quality, collaboration patterns, integration between OSM and authoritative data, use of OSM data in specific domains and applications, reuse of tools created around the project (e.g. for the collaborative mapping) etc. [2], more than directly shaping Citizen Science (CS) projects around OSM. However, despite OSM and (geographical) CS projects have many points of intersection [3] and examples of direct contribution of OSM mappers to CS initiatives exist, the link between them is still largely unexplored. Such link might be relevant in a number of different directions, e.g. the exploration of how OSM data may assist in the development of CS initiatives and complement/enrich data collected by citizens; how CS data may, in turn, be included and improve the OSM database; how OSM best practices and lessons learned throughout the project’s 10+ years of development (about issues such as quality, governance, licensing, sustainability, etc.) may assist in organizing and running CS initiatives."br" This session wants to stimulate the attention and interest from the CS community to the OSM database, its ecosystem of tools and services [4] as well as the OSM community as a fertile ground where CS can build and grow projects from local to international scales."br" The session will be organised as an interactive session where a few panellists will first introduce OSM and its main characteristics and then will present a few use cases where data in OSM can be used in support of CS projects. After that, participants will be encouraged to bring data relevant to their own use cases and work in groups, together with panellists, to evaluate the potential to use OSM with their specific data and projects as well as to contribute data gathered in their CS projects back to the OSM database.
Abstract
OpenStreetMap (OSM, https://www.openstreetmap.org) is currently the largest, richest, most complete and most up-to-date open geospatial database as well as the most participated [...]
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Advanced Driver-Assistance Systems for City Bus Applications
J. Early, R. Douglas, R. Best, L. Blades, C. Lo

Collection of open conferences in research transport (2020). Vol. 2020, 84

Abstract
The bus sector is currently lagging behind when it comes to implementing autonomous systems for improved vehicle safety. However, in cities such as London, public transport strategies are changing, with requirements being made for advanced driver-assistance systems (ADAS) on buses. This study discusses the adoption of ADAS systems within the bus sector. A review of the on-road ADAS bus trials shows that passive forward collision warning (FCW) and intelligent speed assistance (ISA) systems have been successful in reducing the number of imminent pedestrian/vehicle collision events and improving speed limit compliance, respectively. Bus accident statistics for Great Britain have shown that pedestrians account for 82% of all fatalities, with three quarters occurring with frontal bus impacts. These statistics suggest that the bus forward collision warning system is a priority for inclusion in future vehicles to enhance the driver’s direct vision, and to increase reaction time for earlier brake application. Almost 80% of bus occupant casualties occurred in non-impact situations, mainly during acceleration/deceleration events. Therefore, care must be taken in implementing autonomous braking in buses, to ensure that it does not cause an increased number of deceleration events beyond the safe stability limits for passengers. Real on-road drive cycle data has shown that while instances of unsafe braking events do not occur regularly, there are instances of braking events that would present a hazard to both seated and standing passengers, therefore systems that would mitigate these issues would have real benefits to both passenger comfort and safety. During tests to simulate the use of the vehicle retarder for an autonomous braking system, deceleration rates largely remained safely within standee and seated passenger stability limits, whereas an emergency stop test showed a peak deceleration 3.5 times the limit of a standee supported by a vertical handrail, and 4 times the limit for a forward/backward facing seated passenger.
Abstract
The bus sector is currently lagging behind when it comes to implementing autonomous systems for improved vehicle safety. However, in cities such as London, public transport [...]
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Data-Driven Approach for Aircraft Arrival Sequencing Investigation at Terminal Maneuvering Area
T. Klein, R. Liem, G. Lui

Collection of open conferences in research transport (2020). Vol. 2020, 83

Abstract
International audience; Recent air traffic management aims to provide a safety-first operation to support the aircraft approaching and landing procedures. Due to the complexity of air traffic in the terminal control area (also known as the terminal maneuvering area or TMA), simultaneous consideration of aviation economics, environmental concerns, and safety operations in decision makings can be challenging. To improve air traffic controllers' work efficiency and reduce the adverse environmental impact, it is crucial to establish a robust arrival strategy that incorporates weather conditions and flight trajectory configuration. The current state-of-the-art solutions for arrival sequencing and scheduling problem focus more on the operation research aspect, which neglects the airway configuration. Also, no wind condition is assumed to simplify the weather condition. Furthermore, many research efforts have not properly considered practical phenomenon such as holding patterns in their arrival sequencing model, which affects the accuracy of fuel burnt consumption. In this work, we will construct a study on aircraft arrival flow based on historical data at Hong Kong International Airport (HKIA). By extracting features from the data, our results include the spatiotemporal pattern recognition for aircraft arrival transit time and congestion inside HKIA TMA. Besides delivering the statistical analysis on the HKIA aircraft arrival flow, an arrival transit time prediction based on random forest regression is also converted. Results show that our methodologies are not only advantageous in extracting crucial hidden information from historical data for air traffic controllers but also can increase the accuracy of arrival transit time prediction under most of the circumstances.
Abstract
International audience; Recent air traffic management aims to provide a safety-first operation to support the aircraft approaching and landing procedures. Due to the complexity [...]
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The future of urban freight transport: Shifting the cities role from observation to operative steering
T. Otte, A. Fenollar Solvay, T. Meisen

Collection of open conferences in research transport (2020). Vol. 2020, 81
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An Adaptive and Near Parameter-free Evolutionary Computation Approach Towards True Automation in AutoML
B. Evans, M. Zhang, B. Xue

Collection of open conferences in research transport (2020). Vol. 2020, 80

Abstract
common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of this is that there are still hyperparameters which must be tuned in order to achieve good performance. In this work, we propose a near "parameter-free" genetic programming approach, which adapts the hyperparameter values throughout evolution without ever needing to be specified manually. We apply this to the area of automated machine learning (by extending TPOT), to produce pipelines which can effectively be claimed to be free from human input, and show that the results are competitive with existing state-of-the-art which use hand-selected hyperparameter values. Pipelines begin with a randomly chosen estimator and evolve to competitive pipelines automatically. This work moves towards a truly automatic approach to AutoML. Comment: 18 pages (single column), 2 figure
Abstract
common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of this is that there [...]
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ENVIRONMENTAL RISK ASSESSMENT FROM OPERATION OF GAS PIPELINES
A. Hrytsanchuk, L. Poberezhna, L. Poberezhny

Collection of open conferences in research transport (2020). Vol. 2020, 78
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BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab
Y. Jin, H. Yu, F. Li

Collection of open conferences in research transport (2020). Vol. 2020, 77

Abstract
CodaLab is an open-source web-based platform for collaborative computational research. Although CodaLab has gained popularity in the research community, its interface has limited support for creating reusable tools that can be easily applied to new datasets and composed into pipelines. In clinical domain, natural language processing (NLP) on medical notes generally involves multiple steps, like tokenization, named entity recognition, etc. Since these steps require different tools which are usually scattered in different publications, it is not easy for researchers to use them to process their own datasets. In this paper, we present BENTO, a workflow management platform with a graphic user interface (GUI) that is built on top of CodaLab, to facilitate the process of building clinical NLP pipelines. BENTO comes with a number of clinical NLP tools that have been pre-trained using medical notes and expert annotations and can be readily used for various clinical NLP tasks. It also allows researchers and developers to create their custom tools (e.g., pre-trained NLP models) and use them in a controlled and reproducible way. In addition, the GUI interface enables researchers with limited computer background to compose tools into NLP pipelines and then apply the pipelines on their own datasets in a “what you see is what you get” (WYSIWYG) way. Although BENTO is designed for clinical NLP applications, the underlying architecture is flexible to be tailored to any other domains.
Abstract
CodaLab is an open-source web-based platform for collaborative computational research. Although CodaLab has gained popularity in the research community, its interface has [...]
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Getting ready for the future: How can we reach user-centric mobility in Europe by 2030?
I. KESERU, B. MULLER, M. URBAN, E. Foldesi, L. Napoletano, T. COOSEMANS, C. Macharis

Collection of open conferences in research transport (2020). Vol. 2020, 76

Abstract
The Mobility4EU project created a vision for a user-centric and cross-modal European transport system in 2030 and an action plan to implement that vision. We used a combination of creative and analytical methods to come from problem identification to the action plan applying a user-centric methodology that included stakeholders in each step of the process. The Action Plan details measures that address technical topics but especially refer to societal aspects and issues for multi-stakeholder interaction, as e.g. policy, user acceptance, standardization, collaboration and the integration of the user perspective into the R&D&I process. The Action Plan adds to the other similar initiatives by providing recommendations on mainstreaming of universal design and user-centric design processes, synergies and collaboration potential between modes and the combination of transport of passengers and freight building on the quadruple helix model of collaboration between academia, users, industry and policy makers.
Abstract
The Mobility4EU project created a vision for a user-centric and cross-modal European transport system in 2030 and an action plan to implement that vision. We used a combination [...]
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Global and Secured UAV Authentication System based on Hardware-Security
T. Fischer, C. Steger, D. Pirker, C. Lesjak

Collection of open conferences in research transport (2020). Vol. 2020, 75

Abstract
UAVs are gaining traction outside their usual markets of hobbyists, areal recordings, and surveillance services with cloud computing enabled applications and their massive combined computing power. These applications rapidly grow the UAV market, consequently raising the priority of safety solutions. Tremendous incidents, such as the air traffic interruption in London (Dec. 2018), raised awareness and demand for UAV identification, authentication, and tracking. To prevent these type of incidents, aviation authorities, such as the FAA or EASA, are currently working on proper regulations. The implementation of the regulations demands dependable technical solutions. This paper proposes a secured and globally operative UAV authentication system, based on reliable security mechanisms and standardized protocols. Therefore, this system must provide mutual and strong cryptographic authentication. First, the TLS protocol is used for mutual authentication and for protecting the communication. Then, hardware-security is implemented to store the necessary keys and certificates in a protected storage, thus supporting the TLS handshake to avoid common attacks against pure software implementations. Lastly, a concept for protected sensor values is introduced. The proposed UAV authentication concept is demonstrated by a proof-of-concept implementation, evaluated for performance and compared to existing solutions.
Abstract
UAVs are gaining traction outside their usual markets of hobbyists, areal recordings, and surveillance services with cloud computing enabled applications and their massive [...]
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Assessing global OpenStreetMap building completeness to generate large-scale 3D city models
F. Biljecki, L. Ang

Collection of open conferences in research transport (2020). Vol. 2020, 74

Abstract
Biljecki, F., & Ang, M. L. (2020). Assessing Global OpenStreetMap building completeness to generate large-scale 3D city models In: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online Conference, July 4-5 2020. Available at https://zenodo.org/communities/sotm-2020
Abstract
Biljecki, F., & Ang, M. L. (2020). Assessing Global OpenStreetMap building completeness to generate large-scale 3D city models In: Minghini, M., Coetzee, S., Juhász, L., [...]
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Thickened and Paste Tailings Pipeline Systems: Design Procedure – Part 1
R. Cooke

Collection of open conferences in research transport (2020). Vol. 2020, 73

Abstract
The design methodology for pipeline systems conveying thickened and paste tailings systems has been well developed over the last decade. This series of papers outlines the process for designing and implementing a typical surface tailings or underground backfill pipeline system. The papers comprise the following parts: Part 1 (this paper) discusses: o development of the design criteria document, o issues to be considered for the test work, and o pipeline flow behaviour modelling, friction loss calculation and pipe diameter selection. Part 2, to be presented at Paste and Thickened Tailings 2007, will include: o centrifugal pump performance derating, o hydraulic and mechanical design, o operational and control considerations, and o specific considerations for thickener underflow and gravity flow systems. 1.1 Terminology Our company classifies tailings and backfills according to the following criteria: The upper limit for conventional tailings is considered to correspond to the freely settled packing concentration. This typically corresponds to yield stresses of between 5 and 20 Pa. High concentration tailings or thickened tailings is considered to cover the range from the freely settled concentration to the concentration at which the mixture has a fully sheared yield stress corresponding to 100 Pa. Figure 1 illustrates the slump of a mixture with a 100 Pa yield stress. Paste tailings and fill are considered to be mixtures with yield stresses greater than 100 Pa. The practical upper limit for pipeline transport is about 800 Pa. These mixtures may be transported in turbulent or laminar flow: Paste\u00192006\u0019–\u0019R.J.\u0019Jewell,\u0019S.\u0019Lawson,\u0019P.\u0019Newman\u0019(eds)\u0019 ©\u00192006\u0019Australian\u0019Centre\u0019for\u0019Geomechanics,\u0019Perth,\u0019ISBN\u00190-9756756-5-6 Paste\u00192006,\u0019Limerick,\u0019Ireland\u0019 371 Turbulent flow – inertial forces dominate and the friction losses are relatively insensitive to the tailings rheology. Laminar flow – viscous forces dominate and the friction losses are directly related to the tailings rheology, which in turn is strongly effected by the tailings material properties, water chemistry and solids concentration. The transition zone from laminar flow occurs over a range of pipeline flow rates and is characterised by fluctuating pressure gradients. Thickened tailings are typically transported in laminar flow, but turbulent flow operation is possible for low yield stress mixtures, large diameter pipes and high operating velocities. Paste tailings are always transported in laminar flow. Iron ore tailings 64%m, 100 Pa yield stress Figure 1 Slump at transition from high concentration tailings to paste 1.2 Design process The procedure outlined in this paper is a guideline defining the typical steps to be followed when designing a pipeline system transporting thickened tailings or paste. It is not a definitive procedure that can be followed without a suitable background in the field and a proper understanding of thickened and paste tailings flow behaviour. It is also important to note that the design process is iterative in nature. So while the steps have been laid out in an ideal linear path, the reality is that the process will be more chaotic with frequent jumps between the various steps of the process.
Abstract
The design methodology for pipeline systems conveying thickened and paste tailings systems has been well developed over the last decade. This series of papers outlines the [...]
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Sustainable Development as a Basic Concept Development of Cities
V. Kandzija, I. Tolic, P. Cudina

Collection of open conferences in research transport (2020). Vol. 2020, 72

Abstract
The development of cities by their volume and dynamics generated many conflicting places in both conceptual as well as in the implementation part. The sensibility of our time, public sensitivity to the quality of life and environmental quality required in consideration of development concepts for the new approaches. A special dimension to the issue of giving and awareness of the scarcity of resources. The doctrine of sustainable development manifests itself as an epoch-making, and the only way out of the above dilemma. Dimensions that reflect doctrines are improving urban infrastructure and urban infrastructure, support the development of social services and civil society, support local development, energy efficient development - reducing CO2 emissions, preservation and development of cultural heritage, sustainable transport and networking, development cooperation, improving governance. It is necessary to find an answer to the growing needs of urban communities and local governments to take over the role of the driver of economic activity in their communities, organizers of social inclusion and advocate of environmental protection and the fight against climate change. In times of reduced fiscal capacity and growing obligations, the EU structural funds and investment funds are proving to be an important and accessible source of funding for a range of public needs at the local level.
Abstract
The development of cities by their volume and dynamics generated many conflicting places in both conceptual as well as in the implementation part. The sensibility of our time, [...]
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Simulator for the reproduction of "Low Sonic Boom"-signatures
S. Töpken, S. van de Par

Collection of open conferences in research transport (2020). Vol. 2020, 70

Abstract
Supersonic aircraft produce a sonic boom when flying faster than the speed of sound. In order to rule out detrimental"br" e ects for inhabitants of overflown areas, civil supersonic flights (like the Concorde) were allowed to fly over water only."br" Due to progress in aircraft design, the super sonic boom may be reduced considerably in the future. Such ”Low Sonic"br" Boom”-signatures will be considerably quieter and sound completely di erent compared to conventional sonic booms."br" Currently, the sensation and the subjective response of humans to future ”Low Sonic Boom”-signatures is not known."br" For an assessment of human responses to ”Low Sonic Boom”-signatures, a Sonic-Boom simulator has been built at the"br" University of Oldenburg as a pressure chamber with a volume of about 9 m"sup"3"/sup". Two 18” loudspeaker chassis enable the"br" production of an overpressure of up to 20 Pa for a signature duration of 200 ms. The background noise level in the"br" chamber is very low (21 dB(A)) and the chamber has a very small reverberation time of T"sub"20"/sub"=0.2 s averaged over octave"br" bands from 63 Hz to 8 kHz. A vibration platform is installed in the chamber to simulate whole-body vibration that may"br" occur in connection with ”Low Sonic Boom”-signatures.
Abstract
Supersonic aircraft produce a sonic boom when flying faster than the speed of sound. In order to rule out detrimental"br" e ects for inhabitants of overflown areas, civil [...]
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Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
Y. Chen, Y. Kao, Y. Chuang, Y. Liu, M. Yang, W. Lai, J. Huang

Collection of open conferences in research transport (2020). Vol. 2020, 69

Abstract
Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to existing learning-based methods, our core idea is to incorporate the domain knowledge of the LDR image formation pipeline into our model. We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization. We then propose to learn three specialized CNNs to reverse these steps. By decomposing the problem into specific sub-tasks, we impose effective physical constraints to facilitate the training of individual sub-networks. Finally, we jointly fine-tune the entire model end-to-end to reduce error accumulation. With extensive quantitative and qualitative experiments on diverse image datasets, we demonstrate that the proposed method performs favorably against state-of-the-art single-image HDR reconstruction algorithms. Comment: CVPR 2020. Project page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR Code: https://github.com/alex04072000/SingleHDR
Abstract
Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by [...]
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INTEGRATED TRAFFIC CONTROL FOR FREEWAYS USING VARIABLE SPEED LIMITS AND LANE CHANGE CONTROL ACTIONS
V. Markantonakis, I. Papamichail, D. Skoufoulas, M. Papageorgiou

Collection of open conferences in research transport (2020). Vol. 2020, 68

Abstract
The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and comfort, one of the goals is the alleviation of traffic congestion which is a major and challenging problem for modern societies. The paper investigates the combined use of two feedback control strategies utilizing VACS at different penetration rates, aiming to maximize throughput at bottleneck locations. The first control strategy employs mainstream traffic flow control using appropriate variable speed limits as an actuator. The second control strategy delivers appropriate lane-changing actions to selected connected vehicles using a feedback-feedforward control law. Investigations of the proposed integrated scheme have been conducted using a microscopic simulation model for a hypothetical freeway featuring a lane-drop bottleneck. The results demonstrate significant improvements even for low penetration rates of connected vehicles. Document type: Article
Abstract
The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and [...]
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Road Grade Estimation Using Crowd-Sourced Smartphone Data
L. Su, A. Gupta, W. Zhong, C. Qiao, S. Hu, A. Sadek

Collection of open conferences in research transport (2020). Vol. 2020, 67

Abstract
Estimates of road grade/slope can add another dimension of information to existing 2D digital road maps. Integration of road grade information will widen the scope of digital map's applications, which is primarily used for navigation, by enabling driving safety and efficiency applications such as Advanced Driver Assistance Systems (ADAS), eco-driving, etc. The huge scale and dynamic nature of road networks make sensing road grade a challenging task. Traditional methods oftentimes suffer from limited scalability and update frequency, as well as poor sensing accuracy. To overcome these problems, we propose a cost-effective and scalable road grade estimation framework using sensor data from smartphones. Based on our understanding of the error characteristics of smartphone sensors, we intelligently combine data from accelerometer, gyroscope and vehicle speed data from OBD-II/smartphone's GPS to estimate road grade. To improve accuracy and robustness of the system, the estimations of road grade from multiple sources/vehicles are crowd-sourced to compensate for the effects of varying quality of sensor data from different sources. Extensive experimental evaluation on a test route of ~9km demonstrates the superior performance of our proposed method, achieving $5\\times$ improvement on road grade estimation accuracy over baselines, with 90\\% of errors below 0.3$^\\circ$. Comment: Proceedings of 19th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'20)
Abstract
Estimates of road grade/slope can add another dimension of information to existing 2D digital road maps. Integration of road grade information will widen the scope of digital [...]
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Characterizing Radar Network Traffic: a first step towards spoofing attack detection
T. Riberolles, G. Silvestre, N. Larrieu, Y. Zou, J. Song

Collection of open conferences in research transport (2020). Vol. 2020, 66

Abstract
International audience; An Air Traffic Management (ATM) Surveillance System is used to provide services to perform Air Traffic Control (ATC) (e.g., horizontal separation between aircraft). This sytem carries messages containing aircraft's position from a collection of radars of an Air Navigation Service Provider (ANSP) through its network. Then Radar traffic is one of the most important sources of information for this system. The format of the radar messages is defined by a specific application-layer protocol entitled ASTERIX. The evolution of the security policy and technologies used makes existing radar systems, once considered safe, now potentially open to attack. Both safety and security of ATM system could be impacted by any kind of attack into the network traffic, who could maliciously modified information about aicrafts, in particular thanks to Spoofing Attack. To counter this risk, there is need to detect intrusion and then to have anomaly detection modules for this safety-critical network traffic, that can be deployed in a security appliance. In order to design this module, we did a statistical analysis to have an overview of the traffic to better know what we need to protect. Specifically, we studied radar network traffic in order to extract high level statistic characteristics of normal radar traffic. This allowed us to identify a trend in the evolution of this traffic. We were then able to inject a spoofing attack (when a malicious party impersonates another device or network user for the purpose of altering the data) into this traffic to modify the nominal traffic. Thereafter, we were able to detect this attack using our method, which consists of the use of a machine learning detection method, using a Long-Short Term Memory (LSTM) mechanism. This is the subject of our paper, an overview of radar traffic and a method to detect spoofing attack in this traffic. This would help to develop an ATM IDS especially as this type of attack could remain invisible for air traffic controller.
Abstract
International audience; An Air Traffic Management (ATM) Surveillance System is used to provide services to perform Air Traffic Control (ATC) (e.g., horizontal separation between [...]
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Traffic optimization at the Application Level Proof of Concept, development and usefulness evaluation of the ALTO solution
G. Camaz, P. Caldas, P. Sousa

Collection of open conferences in research transport (2020). Vol. 2020, 65

Abstract
This paper presents an overview, proof of concept, and a preliminary demonstrative benchmarking study of the Application-Layer Traffic Optimization (ALTO) architecture proposed by the IETF ALTO Working Group. The main ALTO system purpose is to allow applications to get a more complete view of the underlying network infrastructure, allowing for wellreasoned connection decisions in situations of service redundancy. This paper first begins with a technical description of the ALTO project, and afterwards evaluates how P2P applications, guided by our proposed prototype implementation of the ALTO architecture, perform in comparison to traditional peer selection algorithms on the task of downloading a file in a typical file-sharing P2P network environment. The obtained results from our developed ALTO prototype system state that an application guided by the ALTO solution reduced overall network usage by around 40% with no significant impact in the application performance. FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020
Abstract
This paper presents an overview, proof of concept, and a preliminary demonstrative benchmarking study of the Application-Layer Traffic Optimization (ALTO) architecture proposed [...]
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Resilience of Air Traffic Controllers in control tower
T. Ohashi, M. Kitamura, M. Takahashi, D. Karikawa, H. Aoyama

Collection of open conferences in research transport (2020). Vol. 2020, 64
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Two-Phase Slug Flow Correlations for Severe Slugging in Subsea Pipelines
S. Zendehboudi, G. Naterer, L. Igbokwe

Collection of open conferences in research transport (2020). Vol. 2020, 63
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Innovative Geoinformation Systems for the Design of Communication Paths
G. Viselga, Y. Ugnenko, O. Tymchenko, E. Uzhviieva, N. Sorochuk

Collection of open conferences in research transport (2020). Vol. 2020, 62

Abstract
The article analyses the volume of passenger traffic from 1990 to 2019 for land, water and air transport. From the materials obtained and the experience of the networks of European and world high-speed railways, goals are set. High-speed lines designed exclusively for passenger traffic. This moment plays an important role in reducing the cost of construction, increasing the market and economic profitability. According to the data from the State Statistics Service of Ukraine, it is possible to calculate the passenger flow based on the known parameters for 2020–2032 in the direction of Kiev–Lviv. The design of high-speed lines should meet general requirements aimed at satisfying the basic characteristics of a high-speed railway system, which works in conjunction with the European High-Speed Railway network. The compatibility of the parameters of high-speed lines with the parameters of traditional lines is part of the operational requirements for the gradual introduction of a network of high-speed railways. Possible scenarios to achieve the required compatibility should cover all subsystems. DOI: https://doi.org/10.3846/enviro.2020.693
Abstract
The article analyses the volume of passenger traffic from 1990 to 2019 for land, water and air transport. From the materials obtained and the experience of the networks of [...]
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Security aspects of communications in VANETs
N. Dokuz, M. Ali, S. Mihai, R. Trestian, P. Shah

Collection of open conferences in research transport (2020). Vol. 2020, 60

Abstract
The Fourth Industrial Revolution has begun and it promises breakthroughs in Artificial Intelligence, robotics, Machine Learning, Internet of Things, Digital Twin, and many other technologies that tackle advancements in the industries. The trend is headed towards automation and connectivity. In the automotive industry, advancements have been made towards integrating autonomous driving vehicles into Intelligent Transport Systems (ITS) with the use of Vehicular Ad-Hoc Networks (VANETs). The purpose of this type of network is to enable efficient communication between vehicles (V2V communication) or vehicles and infrastructure (V2I communication), to improve driving safety, to avoid traffic congestion, and to better coordinate transport networks. This direction towards limited (or lack of) human intervention implies vulnerability to cyber attacks. In this context, this paper provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) privacy, 2) authentication and 3) message integrity within VANETs. Discussions, challenges and open issues faced by the current and next generation of vehicular networks are also provided.
Abstract
The Fourth Industrial Revolution has begun and it promises breakthroughs in Artificial Intelligence, robotics, Machine Learning, Internet of Things, Digital Twin, and many [...]
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Video Based Vehicle Counting Using Deep Learning Algorithms
M. J, S. Santhi

Collection of open conferences in research transport (2020). Vol. 2020, 58

Abstract
Traffic density in roads has been increasing day by day which needs intelligent transportation system that can handle the traffic. Traffic management has become inevitable for smart cities. The enormous increase in vehicle numbers has generated more pressure to manage traffic congestion especially during peak hours. If the traffic congestion at a particular point of time can be found, then that information can be useful for managing the traffic in different lanes and change the traffic light cycle dynamically according to the vehicle count in different lanes. In recent years video surveillance and monitoring has been gaining importance. Video can be analyzed which can be used to find the traffic density. Many useful information can be obtained by video processing like real time traffic density. Vehicle counting can be done by detecting the object, tracking it and then finally counting the objects. Many different techniques are available for object detection and tracking. Deep learning techniques for object detection led to remarkable improvements compared to conventional image processing techniques by removing the weakness in the conventional techniques. This paper provides a survey on various techniques available for vehicle detection and tracking.
Abstract
Traffic density in roads has been increasing day by day which needs intelligent transportation system that can handle the traffic. Traffic management has become inevitable [...]
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Vehicle Localization Based on Visual Lane Marking and Topological Map Matching
R. Asghar, C. Laugier, J. Lussereau, M. Garzón

Collection of open conferences in research transport (2020). Vol. 2020, 57

Abstract
urate and reliable localization is crucial to autonomous vehicle navigation and driver assistance systems. This paper presents a novel approach for online vehicle localization in a digital map. Two distinct map matching algorithms are proposed: i) Iterative Closest Point (ICP) based lane level map matching is performed with visual lane tracker and grid map ii) decision-rule based approach is used to perform topological map matching. Results of both the map matching algorithms are fused together with GPS and dead reckoning using Extended Kalman Filter to estimate vehicle’s pose relative to the map. The proposed approach has been validated on real life conditions on an equipped vehicle. Detailed analysis of the experimental results show improved localization using the two aforementioned map matching algorithms.
Abstract
urate and reliable localization is crucial to autonomous vehicle navigation and driver assistance systems. This paper presents a novel approach for online vehicle localization [...]
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Uncertainty Based Camera Model Selection
T. Pajdla, Z. Kukelova, M. Polic, C. Albl, S. Steidl

Collection of open conferences in research transport (2020). Vol. 2020, 56

Abstract
The quality and speed of Structure from Motion (SfM) methods depend significantly on the camera model chosen for the reconstruction. In most of the SfM pipelines, the camera model is manually chosen by the user. In this paper, we present a new automatic method for camera model selection in large scale SfM that is based on efficient uncertainty evaluation. We first perform an extensive comparison of classical model selection based on known Information Criteria and show that they do not provide sufficiently accurate results when applied to camera model selection. Then we propose a new Accuracy-based Criterion, which evaluates an efficient approximation of the uncertainty of the estimated parameters in tested models. Using the new criterion, we design a camera model selection method and fine-tune it by machine learning. Our simulated and real experiments demonstrate a significant increase in reconstruction quality as well as a considerable speedup of the SfM process. Document type: Conference object
Abstract
The quality and speed of Structure from Motion (SfM) methods depend significantly on the camera model chosen for the reconstruction. In most of the SfM pipelines, the camera [...]
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Agent based simulation for the design of a mobility service in the Paris-Saclay area
T. Chouaki, J. Puchinger

Collection of open conferences in research transport (2020). Vol. 2020, 55

Abstract
International audience; Autonomous vehicles promise an important opportunity for a complete paradigm shift for the design of transportation systems. These systems will become more flexible and efficient by adapting to the travelers' demand. On the other hand, multi agent systems offer an intuitive and powerful way to design complex distributed systems and agent based simulation has proved to be well suited for studying the performance of mobility services and their impact on the users and the traffic in general. In this study, we use an Agent-Based modeling approach to design a mobility system based on a fleet of autonomous vehicles (robo-taxis and shuttles) and connected road side units, each of these elements represented by intelligent collaborative agents. In our model, the control is distributed among the agents and the global behaviour of the system emerges from local decisions. We then used a microsimulation tool to test the model on the real road network of the Paris-Saclay area. Since this area is planned to become a center for technology, innovation and education and is currently under constant development, it offers an opportunity for the design and the implementation of new models of transportation services. We designed our mobility system in an incremental manner by introducing more components and more intelligent behaviour and testing its performance at each step. Our results suggest that for our area of study, a mobility service that relies on autonomous vehicles aided by connected road side units that allow to retrieve information about the traffic would perform better than a regular service.
Abstract
International audience; Autonomous vehicles promise an important opportunity for a complete paradigm shift for the design of transportation systems. These systems will become [...]
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Exploring the Potential of Traffic Index Data to Analyze Essential Traffic Impact in Developing Cities
T. Moyo, A. Kibangou, W. Musakwa

Collection of open conferences in research transport (2020). Vol. 2020, 54

Abstract
Abstract. In developing countries, metropolitan cities, due to their economic activities, attract an increasing amount of commuters on a daily basis. This has led to major freeways and roads experiencing high levels of congestion and consequently high pollution levels. In 2020, due to a global pandemic of an outbreak of Corona Virus (COVID-19), the national government declared a national shutdown with only essential traffic being allowed to operate. Given the scenario of the national lock-down this allows for the statistical analysis of the impact of essential traffic on the overall transportation system. Consequently the aim of the paper was to assess the congestion and CO2 emission impact of essential traffic for the City of Johannesburg. Using an exploratory approach, we monitored and collected traffic congestion data from the Tomtom traffic index for the metropolitan city of Johannesburg, South Africa. We develop a relationship between congestion and pollution to visualise the daily variations in pollution and congestion levels. We demonstrate this by comparing variations in congestion levels in two epochs, viz the period without movement restrictions and the period whereby movement is restricted. The results reveal essential traffic on the congestion index to be below 22 percent for both weekends and weekdays. A scenario common only during weekends in 2019. Whilst for the emission index, CO2 levels are approximately less than 45 percent throughout the week. The paper concludes the investment into mining and analysing traffic data has a significantly role for future mobility planning in both the developed and developing world and, more generally, improving the quality of commuting trips in the city. Document type: Article
Abstract
Abstract. In developing countries, metropolitan cities, due to their economic activities, attract an increasing amount of commuters on a daily basis. This has led to major [...]
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High-Resolution Augmentation for Automatic Template-Based Matching of Human Models
E. Rodolà, R. Marin, S. Melzi, U. Castellani

Collection of open conferences in research transport (2020). Vol. 2020, 52

Abstract
We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: an intrinsic spectral matching pipeline, a morphable model, and an extrinsic details refinement. By operating in conjunction, these tools allow us to greatly improve the quality of the matching while at the same time resolving the key issues exhibited by each tool individually. In this paper we present an innovative High-Resolution Augmentation (HRA) strategy that enables highly accurate correspondence even in the presence of significant mesh resolution mismatch between the input shapes. This augmentation provides an effective workaround for the resolution limitations imposed by the adopted morphable model. The HRA in its global and localized versions represents a novel refinement strategy for surface subdivision methods. We demonstrate the accuracy of the proposed pipeline on multiple challenging benchmarks, and showcase its effectiveness in surface registration and texture transfer.
Abstract
We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: an intrinsic spectral matching [...]
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Learning by Analogy: Reliable Supervision From Transformations for Unsupervised Optical Flow Estimation
Y. Liu, J. Li, D. Luo, L. Liu, R. He, C. Wang, J. Zhang, Y. Tai, W. Yabiao, F. Huang

Collection of open conferences in research transport (2020). Vol. 2020, 51

Abstract
Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods. However, the objective of unsupervised learning is likely to be unreliable in challenging scenes. In this work, we present a framework to use more reliable supervision from transformations. It simply twists the general unsupervised learning pipeline by running another forward pass with transformed data from augmentation, along with using transformed predictions of original data as the self-supervision signal. Besides, we further introduce a lightweight network with multiple frames by a highly-shared flow decoder. Our method consistently gets a leap of performance on several benchmarks with the best accuracy among deep unsupervised methods. Also, our method achieves competitive results to recent fully supervised methods while with much fewer parameters. Comment: Accepted to CVPR 2020, https://github.com/lliuz/ARFlow
Abstract
Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods. However, the objective [...]
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Approach and landing aircraft on-board parameters estimation with LSTM networks
D. Delahaye, E. Feron, G. Jarry

Collection of open conferences in research transport (2020). Vol. 2020, 50

Abstract
International audience; This paper addresses the problem of estimating aircraft on-board parameters using ground surveillance available parameters. The proposed methodology consists in training supervised Neural Networks with Flight Data Records to estimate target parameters. This paper investigates the learning process upon three case study parameters: the fuel flow rate, the flap configuration, and the landing gear position. Particular attention is directed to the generalization to different aircraft types and airport approaches. From the Air Traffic Management point of view, these additional parameters enable a better understanding and awareness of aircraft behaviors. These estimations can be used to evaluate and enhance the air traffic management system performance in terms of safety and efficiency.
Abstract
International audience; This paper addresses the problem of estimating aircraft on-board parameters using ground surveillance available parameters. The proposed methodology [...]
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Dynamic Hot Spot Prediction by Learning Spatial- Temporal Utilization of Taxiway Intersections
H. Ali, M. Schultz, R. Delair, S. Alam, D. Pham

Collection of open conferences in research transport (2020). Vol. 2020, 49

Abstract
International audience; Airports across the world are expanding by building multiple ground control towers and resorting to complex taxiway and runway system, in response to growing air traffic. Current outcome- based ground safety management at the airside may impede our potential to learn from and adapt to evolving air traffic scenarios, owing to the sparsity of accidents when compared with number of daily airside operations. To augment airside ground safety at Singapore Changi airport, in this study, we predict dynamic hot spots- areas where multiple aircraft may come in close vicinity on taxiways, as pre-cursor events to airside conflicts. We use airside infrastructure and A-SMGCS operations data of Changi airport to model aircraft arrival at different taxiway intersections both in temporal and spatial dimensions. The statistically learnt spatial-temporal model is then used to compute conflict probability at identified intersections, in order to evaluate conflict coefficients or hotness values of hot spots. These hot spots are then visually displayed on the aerodrome diagram for heightened attention of ground ATCOs. In the Subjective opinion of Ground Movement Air Traffic Controller, highlighted Hot Spots make sense and leads to better understanding of taxiway movements and increased situational awareness. Future research shall incorporate detailed human-in-the-loop validation of the dynamic hot spot model by ATCOs in 360 degree tower simulator.
Abstract
International audience; Airports across the world are expanding by building multiple ground control towers and resorting to complex taxiway and runway system, in response [...]
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Solving Aircraft Conflicts: data resources
L. Lapasset, M. Rahman, J. Mothe

Collection of open conferences in research transport (2020). Vol. 2020, 47

Abstract
International audience; In the domain of air traffic, two planes are considered as in a conflict situation when their trajectoriescross each other in certain circumstances of distance at the same time. Air Traffic Management(ATM) has adopted some rules to avoid such conflicts but the increasing density of aircraft flightsmakes conflict situations more and more difficult to anticipate and solve in an optimal way. Decisionsto solve conflicts are made manually in real-time and consist of changing aircraft trajectories tomaintain a safe distance between planes. When a conflict is identified, the Air Traffic Controller(ATCO) has to make a quick decision about the best possible solution using his/her knowledge andexperience. ATCOs have to take into account all the aircraft flight parameters such as its speed,positioning coordinate, destination, flight plan, as well as its environment, for example, weather,wind direction, military zone, etc. and the other flights. The air traffic growth is so that the ATCOs willnot be able to face conflict solving in the future if they are not assisted effectively. Moreconsideration should thus be given to (a) identifying conflict situations (b) assist ATCOs in conflictsolving. Many organizations keep data that could serve these challenges but data from similators canalso be used.In this communication, we will present the context of aircraft conflicts. We will detail the datasources that are available and that could be used for conflict detection and automated conflictsolving. Moreover, we will present the data collection we built as a new resource for simulated datathat we intend to deliver to the scientific community as a shared data source.
Abstract
International audience; In the domain of air traffic, two planes are considered as in a conflict situation when their trajectoriescross each other in certain circumstances [...]
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A Methodological Framework of Human-Machine Co-Evolutionary Intelligence for Decision-Making Support of ATM
X. Hu

Collection of open conferences in research transport (2020). Vol. 2020, 46

Abstract
International audience; Despite of the success of artificial intelligent (AI) methods in many domains, there is big dilemma for AI when applying to air traffic management (ATM). That is AI researchers have long stated their AI methods are effective and reliable enough to handle many ATM problems, while human controllers still refuse to adopt such AI methods. We believe the dilemma is not about whether AI methods is effective or reliable enough, but about why human controllers should be replaced by AI methods. In other words, as long as an AI method aims to compete and replace human controllers, it will be confronted with the difficulty of not being accepted by human controllers. To address this dilemma, this paper proposes a new thinking about applying AI methods, i.e., an AI method should be developed in such a way of assisting human controllers, but never in the way of competing and replacing human controllers. This new thinking is called human-machine coevolutionary intelligence (HMCEI). A methodological framework of HMCEI is further developed for decision-making support of ATM, in order to demonstrate the concept of HMCEI is practicably possible.
Abstract
International audience; Despite of the success of artificial intelligent (AI) methods in many domains, there is big dilemma for AI when applying to air traffic management [...]
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Increasing Traffic Flows with DSRC Technology: Field Trials and Performance Evaluation
S. AlGhamisi, A. AlMhanna, K. Al-Ghoneim, M. Alsaleh, I. Ozgunes, A. Alarifi, O. Talabay, L. Basseto, H. Aldossary, A. Jaiprakash, S. Hassen, I. AIKurtass, A. Biyabani, F. Schmutz, A. Pomini, O. Tonguz, R. Zhang, K. Gerard

Collection of open conferences in research transport (2020). Vol. 2020, 45

Abstract
traffic congestion becomes a huge problem for most developing and developed countries across the world, intelligent transportation systems (ITS) are becoming a hot topic that is attracting attention of researchers and the general public alike. In this paper, we demonstrate a specific implementation of an ITS system whereby traffic lights are actuated by DSRC radios installed in vehicles. More specifically, we report the design of prototype of a DSRC-Actuated Traffic Lights (DSRC-ATL) system. It is shown that this system can reduce the travel time and commute time significantly, especially during rush hours. Furthermore, the results reported in this paper do not assume or require all vehicles to be equipped with DSCR radios. Even with low penetration ratios, e.g., when only 20% of all vehicles in a city are equipped with DSRC radios, the overall performance of the designed system is superior to the current traffic control systems. Comment: 5 pages, 9 figures, submitted to the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON 2018), special session of Connected-and-Automated Vehicle Integration, Safety, and Environment Design, on June 30, 2018
Abstract
traffic congestion becomes a huge problem for most developing and developed countries across the world, intelligent transportation systems (ITS) are becoming a hot topic that [...]
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Semantic Management of Urban Traffic Congestion
R. Juric, A. Shakil

Collection of open conferences in research transport (2020). Vol. 2020, 44
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Efficient Transport Logistics : An Approach for Urban Freight Transport in Austria
V. Brandstatter, C. Olaverri-Monreal

Collection of open conferences in research transport (2020). Vol. 2020, 43

Abstract
To alleviate traffic congestion that results from the growth of e-commerce we propose an approach in the city of Linz, Austria by relying on shared distribution centers from different companies. We develop two algorithms to find out the optimal location for the hubs and calculate the shortest path between locations. Results showed that in an urban environment, the implementation of hubs results in a reduction of the number of delivery vehicles. It reduces driving distances from hub to the customers, and also benefits the drivers that need to return home every day. Comment: 6 pages, 5 figures, 2 Tables, accepted for publication in the proceedings of the CISTI'2020 - 15th Iberian Conference on Information Systems and Technologie
Abstract
To alleviate traffic congestion that results from the growth of e-commerce we propose an approach in the city of Linz, Austria by relying on shared distribution centers from [...]
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Estimating Model Uncertainty of Neural Networks in Sparse Information Form
J. Lee, M. Humt, J. Feng, R. Triebel

Collection of open conferences in research transport (2020). Vol. 2020, 42

Abstract
We present a sparse representation of model uncertainty for Deep Neural Networks (DNNs) where the parameter posterior is approximated with an inverse formulation of the Multivariate Normal Distribution (MND), also known as the information form. The key insight of our work is that the information matrix, i.e. the inverse of the covariance matrix tends to be sparse in its spectrum. Therefore, dimensionality reduction techniques such as low rank approximations (LRA) can be effectively exploited. To achieve this, we develop a novel sparsification algorithm and derive a cost-effective analytical sampler. As a result, we show that the information form can be scalably applied to represent model uncertainty in DNNs. Our exhaustive theoretical analysis and empirical evaluations on various benchmarks show the competitiveness of our approach over the current methods. Comment: Accepted to the Thirty-seventh International Conference on Machine Learning (ICML) 2020
Abstract
We present a sparse representation of model uncertainty for Deep Neural Networks (DNNs) where the parameter posterior is approximated with an inverse formulation of the Multivariate [...]
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Development of Methodological Approaches to the Planning of Operation of Road Transport Systems
L. Trofimova

Collection of open conferences in research transport (2020). Vol. 2020, 41
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High precision indoor positioning by means of LiDAR
A. García, M. Botsch, E. Sanchez, B. Huber

Collection of open conferences in research transport (2020). Vol. 2020, 40

Abstract
The trend towards autonomous driving and the continuous research in the automotive area, like Advanced Driver Assistance Systems (ADAS), requires an accurate localization under all circumstances. An accurate estimation of the vehicle state is a basic requirement for any trajectory-planning algorithm. Still, even when the introduction of the GPS L5 band promises lane-accuracy, coverage limitations in roofed areas still have to be addressed. In this work, a method for high precision indoor positioning using a LiDAR is presented. The method is based on the combination of motion models with LiDAR measurements, and uses infrastructural elements as positioning references. This allows to estimate the orientation, velocity over ground and position of a vehicle in a Local Tangent Plane (LTP) reference frame. When the outputs of the proposed method are compared to those of an Automotive Dynamic Motion Analyzer (ADMA), mean errors of 1 degree, 0.1 m/s and of 4.7 cm respectively are obtained. The method can be implemented by using a LiDAR sensor as a stand-alone unit. A median runtime of 40.77 us on an Intel i7-6820HQ CPU signals the possibility of real-time processing.
Abstract
The trend towards autonomous driving and the continuous research in the automotive area, like Advanced Driver Assistance Systems (ADAS), requires an accurate localization [...]
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Travel Time Prediction using Machine Learning and Weather Impact on Traffic Conditions
A. Khan, B. Deb, K. Hasan, S. Khan, M. Alam

Collection of open conferences in research transport (2020). Vol. 2020, 39

Abstract
The growth of Intelligent Traffic System (ITS) have recently been quite fast and impressive. Analysis and prediction of network traffic has become a priority in day to day planning in social, economic and more widespread set of areas. With a vision to further contribute to this vast field of research, we propose an approach to forecast level of traffic congestion on the basis of a time series analysis of collected data using machine learning. Moreover, the proposed approach allows us to find a correlation between varying parameter of weather and level of traffic congestion. Traffic data collected from Uber Movement for the city of Mumbai, India was fed to multiple of pre assessed machine learning algorithm. Comparative analysis of the results of the different machine learning algorithms used have shown us that logistic regression works best with an accuracy of 85% on the collected Uber data. Thus our model can accurately predict the time to travel between different nodes (locations) in Mumbai city based on the data collected from Uber Movement.
Abstract
The growth of Intelligent Traffic System (ITS) have recently been quite fast and impressive. Analysis and prediction of network traffic has become a priority in day to day [...]
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Online Variant of Parcel Allocation in Last-Mile Delivery
X. Bao, Y. Liang, C. Mao

Collection of open conferences in research transport (2020). Vol. 2020, 38

Abstract
We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics parcels. Current existing approaches mainly focus on offline scenarios, where all the spatial-temporal information of parcels and workers are given. However, the offline scenarios can be impractical since parcels and workers appear dynamically in reality, and the information of workers is unknown in advance. In this paper, we study the problem of last-mile delivery on online scenarios to resolve the shortcomings of the offline setting. We first formalize the online parcel allocation in last-mile delivery problem, where all parcels were put in pop-stations in advance, and workers arrive dynamically. Then we propose a baseline algorithm with no competitive ratio, and an algorithm providing theoretical guarantee for the parcel allocation in last-mile delivery. Finally, we verify the effectiveness and efficiency of proposed algorithms through extensive experiments on real and synthetic datasets.
Abstract
We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics parcels. Current [...]
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Application of game theory in planning passenger rail and road transport on parallel routes
S. Stoilova

Collection of open conferences in research transport (2020). Vol. 2020, 37
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O-007 An analysis of stroke thrombectomy interhospital transportation modality
A. Vargas, M. Chen, R. Crowley, A. Beer-Furlan, J. Connors, H. Dasenbrock

Collection of open conferences in research transport (2020). Vol. 2020, 36

Abstract
Objective Expeditious interhospital transport of patients with potential large-vessel occlusions is key in the hub and spoke model, where patients are first taken to a local primary hospital to be evaluated for intravenous thrombolysis, and then subsequently transferred to an endovascular capable stroke center. The decision on transport modality—air versus ground transportation—may be multifactorial, dependent upon dispatch times, availability, and cost. This study aims to evaluate and quantify the presumed reduction in time to thrombectomy with air compared to ground transport. Methods Patients undergoing mechanical thrombectomy for carotid circulation occlusion within 6 hours at an urban, comprehensive stroke center were retrospectively analyzed. Multivariable linear regression evaluated the relationship between transport modality and the time from last known well to groin puncture after adjusting for distance from the comprehensive stroke center. Results From January 2015 to March 2018, 133 mechanical thrombectomy interhospital transfers were identified; transportation modality was air in 30.8% (n=41) and ground in 69.2% (n=92). The mean inter-hospital distance was 24.1 (standard deviation 16.4, range 0–62) miles. Among patients travelling greater than 10 miles, the use of air transport was associated with a significantly shorter time between last known well and groin puncture when compared to ground (by 26.3 minutes, 95% CI: 1.1–51.9 minutes, p=0.04). The benefit of air transport was greater with increasing distances, with a significantly shorter time to thrombectomy of 35.1 minutes (p=0.02) if an inter-hospital distance of greater than 20 miles, and of 42.2 minutes (p=0.03) if greater than 30 miles. Within 10 miles however, all patients were transported by ground. Conclusions In this single-center analysis, helicopter emergency medical service lead to a shorter time to thrombectomy compared with ground transport. Given the known benefit to earlier revascularization on stroke outcomes, these data support the use of emergency aeromedical services when logistically feasible for stroke thrombectomy interhospital transfers greater than 10 miles. Disclosures H. Dasenbrock: None. A. Beer-Furlan: None. A. Vargas: None. J. Connors: None. R. Crowley: None. M. Chen: 2; C; Genentech, Pneumbra, Stryker, Medtronic.
Abstract
Objective Expeditious interhospital transport of patients with potential large-vessel occlusions is key in the hub and spoke model, where patients are first taken to a local [...]
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A Retinex based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images
P. Ekanayaka, S. Sritharan, R. Godaliyadda, H. Weligampola, V. Herath, R. Ragel, G. Jayatilaka

Collection of open conferences in research transport (2020). Vol. 2020, 35

Abstract
Low light image enhancement is an important challenge for the development of robust computer vision algorithms. The machine learning approaches to this have been either unsupervised, supervised based on paired dataset or supervised based on unpaired dataset. This paper presents a novel deep learning pipeline that can learn from both paired and unpaired datasets. Convolution Neural Networks (CNNs) that are optimized to minimize standard loss, and Generative Adversarial Networks (GANs) that are optimized to minimize the adversarial loss are used to achieve different steps of the low light image enhancement process. Cycle consistency loss and a patched discriminator are utilized to further improve the performance. The paper also analyses the functionality and the performance of different components, hidden layers, and the entire pipeline.
Abstract
Low light image enhancement is an important challenge for the development of robust computer vision algorithms. The machine learning approaches to this have been either unsupervised, [...]
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ANALYSIS OF EXISTING PASSENGER TRAFFIC BY MODE OF TRANSPORT AND ASSESSMENT THE COMPETITIVENESS HIGH-SPEED TRAFFIC IN UKRAINE
G. Viselga, N. Bugaec, A. Shevchenko, N. Murygina, Y. Korostelov

Collection of open conferences in research transport (2020). Vol. 2020, 34

Abstract
The article analyses the volume of passenger traffic from 1990 to 2019 for land, water and air transport. From the materials obtained and the experience of the networks of European and world high-speed railways, goals are set. High-speed lines designed exclusively for passenger traffic. This moment plays an important role in reducing the cost of construction, increasing the market and economic profitability. According to the data from the State Statistics Service of Ukraine, it is possible to calculate the passenger flow based on the known parameters for 2020–2032 in the direction of Kiev-Lviv. The design of high-speed lines should meet general requirements aimed at satisfying the basic characteristics of a high-speed railway system, which works in conjunction with the European High-Speed Railway network. The compatibility of the parameters of high-speed lines with the parameters of traditional lines is part of the operational requirements for the gradual introduction of a network of high-speed railways. Possible scenarios to achieve the required compatibility should cover all subsystems. DOI: https://doi.org/10.3846/enviro.2020.689
Abstract
The article analyses the volume of passenger traffic from 1990 to 2019 for land, water and air transport. From the materials obtained and the experience of the networks of [...]
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Recharge at lunch, an alternative to handle the range issues of electric vehicles
D. Cortés-Murcia, H. Afsar, C. Prodhon

Collection of open conferences in research transport (2020). Vol. 2020, 33

Abstract
International audience
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Applying Enterprise Architecture for Digital Transformation of Electro Mobility towards Sustainable Transportation
B. Anthony

Collection of open conferences in research transport (2020). Vol. 2020, 32

Abstract
Electro Mobility (eMobility) involves deploying Information and Communication Technologies (ICT) and electric technologies in vehicles to enable electric propulsion of vehicles referred to as Electric Vehicles (EVs). EVs are key infrastructure for achieving a sustainable energy future since EV usage can support in achieving CO2 reduction. However, the deployment of EVs for eMobility is highly dependent on data integration of mobility solutions from different stakeholders involved in urban transportation. Respectively, data integration from different mobility services will result to cost reduction and create valued added services to citizens. Therefore, there is need to achieve data integration not only for physical systems but for all domains in providing mobility related services that can be synergically applied to citizens and stakeholders in order to develop innovative solutions at district and urban level. Therefore, this study adopts Enterprise Architecture (EA) for digital transformations of eMobility services for sustainable transportation. Action research methodology was employed and secondary data from the literature was presented in the industrial data space reference architecture to initially validate digital transformation of electro mobility. Findings from this study reveal that EA support digital transformation of eMobility in managing data integration to support cities to implement sustainable transportation services. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. SIGMIS-CPR '20, June 19–21, 2020, Nuremberg, Germany © 2020 Association for Computing Machinery. ACM ISBN 978-1-4503-7130-8/20/06…$15.00 https://doi.org/10.1145/3378539.3393858
Abstract
Electro Mobility (eMobility) involves deploying Information and Communication Technologies (ICT) and electric technologies in vehicles to enable electric propulsion of vehicles [...]
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Developing a Traffic Congestion Model based on Google Traffic Data: A Case Study in Ecuador
Y. García-Ramírez

Collection of open conferences in research transport (2020). Vol. 2020, 31
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Exploring Spiking Neural Networks for Prediction of Traffic Congestion in Networks-on-Chip
L. McDaid, J. Liu, J. Harkin, A. Javed

Collection of open conferences in research transport (2020). Vol. 2020, 30
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Should I Stay or Should I Go? Automated Vehicles in the Age of Climate Change
S. Borojeni, A. Kun, B. Donmez, C. Remy, A. Meschtscherjakov, C. Janssen, A. Riener, W. Ju, P. Wintersberger, B. Pfleging

Collection of open conferences in research transport (2020). Vol. 2020, 29

Abstract
Will automated driving help or hurt our efforts to remedy climate change? The overall impact of transportation and mobility on the global ecosystem is clear: changes to that system can greatly affect climate outcomes. The design of mobility and automotive systems will influence key factors such as driving style, fuel choice, ride sharing, traffic patterns, and total mileage. However, to date, there are few research efforts that explicitly focus on these overlapping themes (automated driving & climate changes) within the HCI and AutomotiveUI communities. Our intention is to grow this community and awareness of the related problems. Specifically, in this workshop, we invite designers, researchers, and practitioners from the sustainable HCI, persuasive design, AutomotiveUI, and mobility communities to collaborate in finding ways to make future mobility more sustainable. Using embodied design improvisation and design fiction methods, we will explore the ways that systems affect behavior which then affect the environment.
Abstract
Will automated driving help or hurt our efforts to remedy climate change? The overall impact of transportation and mobility on the global ecosystem is clear: changes to that [...]
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Debugging Machine Learning Pipelines
D. Shasha, R. Lourenço, J. Freire

Collection of open conferences in research transport (2020). Vol. 2020, 27

Abstract
Machine learning tasks entail the use of complex computational pipelines to reach quantitative and qualitative conclusions. If some of the activities in a pipeline produce erroneous or uninformative outputs, the pipeline may fail or produce incorrect results. Inferring the root cause of failures and unexpected behavior is challenging, usually requiring much human thought, and is both time-consuming and error-prone. We propose a new approach that makes use of iteration and provenance to automatically infer the root causes and derive succinct explanations of failures. Through a detailed experimental evaluation, we assess the cost, precision, and recall of our approach compared to the state of the art. Our source code and experimental data will be available for reproducibility and enhancement. Comment: 10 page
Abstract
Machine learning tasks entail the use of complex computational pipelines to reach quantitative and qualitative conclusions. If some of the activities in a pipeline produce [...]
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Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment
M. El-Sharkawy, R. Chappa

Collection of open conferences in research transport (2020). Vol. 2020, 26

Abstract
Convolution neural network is being used in field of autonomous driving vehicles or driver assistance systems (ADAS), and has achieved great success. Before the convolution neural network, traditional machine learning algorithms helped the driver assistance systems. Currently, there is a great exploration being done in architectures like MobileNet, SqueezeNext & SqueezeNet. It improved the CNN architectures and made it more suitable to implement on real-time embedded systems. This paper proposes an efficient and a compact CNN to ameliorate the performance of existing CNN architectures. The intuition behind this proposed architecture is to supplant convolution layers with a more sophisticated block module and to develop a compact architecture with a competitive accuracy. Further, explores the bottleneck module and squeezenext basic block structure. The state-of-the-art squeezenext baseline architecture is used as a foundation to recreate and propose a high performance squeezenext architecture. The proposed architecture is further trained on the CIFAR-10 dataset from scratch. All the training and testing results are visualized with live loss and accuracy graphs. Focus of this paper is to make an adaptable and a flexible model for efficient CNN performance which can perform better with the minimum tradeoff between model accuracy, size, and speed. Having a model size of 0.595MB along with accuracy of 92.60% and with a satisfactory training and validating speed of 9 seconds, this model can be deployed on real-time autonomous system platform such as Bluebox 2.0 by NXP.
Abstract
Convolution neural network is being used in field of autonomous driving vehicles or driver assistance systems (ADAS), and has achieved great success. Before the convolution [...]
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Acceleration of the Pair-HMM forward algorithm on FPGA with cloud integration for GATK
Y. Thoma, R. Wertenbroek

Collection of open conferences in research transport (2020). Vol. 2020, 22

Abstract
The Pair-HMM forward algorithm is an essential algorithm found in many genomic related analyses. The high number of floating point operations in the algorithm makes it one of the main contributors to the compute time of analysis pipelines. To speed-up computations we propose an FPGA-based hardware accelerator for the Amazon AWS F1 Cloud platform. The accelerator is open source and has been tested within the popular Genomic Analysis Toolkit (GATK) pipeline. The accelerator achieved up to 15 × speed-up against the software implementation when used in-pipeline. The accelerator has also been tested in the experimental Spark (distributed) version of the GATK HaplotypeCaller tool. An in-depth analysis of the compute time contributions allowed to point out the main bottlenecks for accelerators in the GATK pipeline, resulting in a hybrid CPU-FPGA solution to best exploit both resources.
Abstract
The Pair-HMM forward algorithm is an essential algorithm found in many genomic related analyses. The high number of floating point operations in the algorithm makes it one [...]
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LiDAR-enhanced Structure-from-Motion
Y. Hu, W. Zhen, H. Yu, S. Scherer

Collection of open conferences in research transport (2020). Vol. 2020, 21

Abstract
hough Structure-from-Motion (SfM) as a maturing technique has been widely used in many applications, state-of-the-art SfM algorithms are still not robust enough in certain situations. For example, images for inspection purposes are often taken in close distance to obtain detailed textures, which will result in less overlap between images and thus decrease the accuracy of estimated motion. In this paper, we propose a LiDAR-enhanced SfM pipeline that jointly processes data from a rotating LiDAR and a stereo camera pair to estimate sensor motions. We show that incorporating LiDAR helps to effectively reject falsely matched images and significantly improve the model consistency in large-scale environments. Experiments are conducted in different environments to test the performance of the proposed pipeline and comparison results with the state-of-the-art SfM algorithms are reported.
Abstract
hough Structure-from-Motion (SfM) as a maturing technique has been widely used in many applications, state-of-the-art SfM algorithms are still not robust enough in certain [...]
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Withdrawal: Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems
T. Lauderdale, T. Nguyen, A. Sadovsky, Y. Zheng, J. D'Amore, J. Phillips, S. Zelinski, Y. Chu, R. Windhorst

Collection of open conferences in research transport (2020). Vol. 2020, 20
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UAS Based Methodology for Measuring Glide Slope Angles of Airport Precision Approach Path Indicators (PAPI)
A. Habib, D. Horton, J. Bullock, Y. Lin, A. Baxmeyer, S. Hasheminasab, D. Bullock

Collection of open conferences in research transport (2020). Vol. 2020, 19

Abstract
The Precision Approach Path Indicator (PAPI) is a Visual Glide Slope Indicator that uses a two-color light projector system to produce a visual glidepath for pilots approaching a runway. This paper reports on a methodology for using an Unmanned Aircraft System (UAS) to measure angles where PAPI lights transition from white to red to assess compliance with the US Federal Aviation Administration (FAA) Order JO6850.2B. The UAS captured images from a series of elevations at varying distances from the PAPI lights on runway 10 at the Purdue University Airport on June 27, 2019. Precise location of each image was obtained by mounting a survey prism on the UAS and using ground-based surveying total stations to record the x, y, z location of the UAS. Two 15-minute UAS missions collected 70 images that were synchronized with total station readings. UAS images were classified by the number of white and red PAPI lights visible. A logit model was used to estimate the glidepath transition angle of the four PAPI Light Housing Assemblies, which were compared with the angle and tolerance of transition angles defined in FAA Order JO6850.2B. A second independent robotic total station measured the location of the UAS when images were taken. Comparing the two independent total station measurements, the root mean squared error of the UAS position on the glide slope was 1.3 arc-min. The paper concludes that low cost UAS with a total station can quickly and accurately evaluate PAPI lights to determine if they are aimed within the prescribed FAA tolerance.
Abstract
The Precision Approach Path Indicator (PAPI) is a Visual Glide Slope Indicator that uses a two-color light projector system to produce a visual glidepath for pilots approaching [...]
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Learning multiview 3D point cloud registration
C. Zhou, T. Birdal, Z. Gojcic, L. Guibas, J. Wegner

Collection of open conferences in research transport (2020). Vol. 2020, 18

Abstract
We present a novel, end-to-end learnable, multiview 3D point cloud registration algorithm. Registration of multiple scans typically follows a two-stage pipeline: the initial pairwise alignment and the globally consistent refinement. The former is often ambiguous due to the low overlap of neighboring point clouds, symmetries and repetitive scene parts. Therefore, the latter global refinement aims at establishing the cyclic consistency across multiple scans and helps in resolving the ambiguous cases. In this paper we propose, to the best of our knowledge, the first end-to-end algorithm for joint learning of both parts of this two-stage problem. Experimental evaluation on well accepted benchmark datasets shows that our approach outperforms the state-of-the-art by a significant margin, while being end-to-end trainable and computationally less costly. Moreover, we present detailed analysis and an ablation study that validate the novel components of our approach. The source code and pretrained models are publicly available under https://github.com/zgojcic/3D_multiview_reg. Comment: CVPR2020 - Camera Ready
Abstract
We present a novel, end-to-end learnable, multiview 3D point cloud registration algorithm. Registration of multiple scans typically follows a two-stage pipeline: the initial [...]
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AUTOTRACKER: Autonomous inspection — capabilities and lessons learned in offshore operations
B. Privat, N. Johnson, J. Evans, C. Capus, P. Patron

Collection of open conferences in research transport (2020). Vol. 2020, 17

Abstract
This paper presents AUTOTRACKER, an autonomous pipeline inspection system that operates as a dynamic mission payload for an Autonomous Underwater Vehicle (AUV). The paper describes the mode of operation, together with the validation & trial operations AUTOTRACKER has undertaken over the years, and how this valuable experience has been fed back into the future development of the system.
Abstract
This paper presents AUTOTRACKER, an autonomous pipeline inspection system that operates as a dynamic mission payload for an Autonomous Underwater Vehicle (AUV). The paper [...]
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Group-In: Group Inference from Wireless Traces of Mobile Devices
J. Fürst, F. Wu, G. Solmaz, S. Aytaç

Collection of open conferences in research transport (2020). Vol. 2020, 16

Abstract
This paper proposes Group-In, a wireless scanning system to detect static or mobile people groups in indoor or outdoor environments. Group-In collects only wireless traces from the Bluetooth-enabled mobile devices for group inference. The key problem addressed in this work is to detect not only static groups but also moving groups with a multi-phased approach based only noisy wireless Received Signal Strength Indicator (RSSIs) observed by multiple wireless scanners without localization support. We propose new centralized and decentralized schemes to process the sparse and noisy wireless data, and leverage graph-based clustering techniques for group detection from short-term and long-term aspects. Group-In provides two outcomes: 1) group detection in short time intervals such as two minutes and 2) long-term linkages such as a month. To verify the performance, we conduct two experimental studies. One consists of 27 controlled scenarios in the lab environments. The other is a real-world scenario where we place Bluetooth scanners in an office environment, and employees carry beacons for more than one month. Both the controlled and real-world experiments result in high accuracy group detection in short time intervals and sampling liberties in terms of the Jaccard index and pairwise similarity coefficient. Comment: This work has been funded by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT and No.871249 LOCUS projects. The content of this paper does not reflect the official opinion of the EU. Responsibility for the information and views expressed therein lies entirely with the authors. Proc. of ACM/IEEE IPSN'20, 2020
Abstract
This paper proposes Group-In, a wireless scanning system to detect static or mobile people groups in indoor or outdoor environments. Group-In collects only wireless traces [...]
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Editorial : OpenStreetMap research in the COVID-19 era
M. Minghini, S. Coetzee, A. Grinberger, G. Yeboah, L. Juhász, P. Mooney

Collection of open conferences in research transport (2020). Vol. 2020, 15

Abstract
Minghini, M., Coetzee, S., Grinberger, A. Y., Yeboah, G., Juhász, L., & Mooney, P. (2020). Editorial: OpenStreetMap research in the COVID-19 era In: Minghini, M., Coetzee, S., Juhász, L., Yeboah, G., Mooney, P., Grinberger, A.Y. (Eds.). Proceedings of the Academic Track at the State of the Map 2020 Online Conference, July 04-05 2020. Available at https://zenodo.org/communities/sotm-2020
Abstract
Minghini, M., Coetzee, S., Grinberger, A. Y., Yeboah, G., Juhász, L., & Mooney, P. (2020). Editorial: OpenStreetMap research in the COVID-19 era In: Minghini, M., Coetzee, [...]
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Materials Cloud, a platform for open computational science
M. Borelli, L. Talirz, E. Passaro, N. Marzari, C. Pignedoli, C. Pignedoli, A. Yakutovich, S. Zoupanos, D. Passerone, D. Passerone, C. Andersen, O. Schütt, O. Schütt, J. VandeVondele, J. VandeVondele, G. Pizzi, F. Gargiulo, T. Schulthess, T. Schulthess, S. Huber, V. Granata, B. Smit, S. Kumbhar, C. Adorf, M. Uhrin

Collection of open conferences in research transport (2020). Vol. 2020, 13

Abstract
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts 1) archival and dissemination services for raw and curated data, together with their provenance graph, 2) modelling services and virtual machines, 3) tools for data analytics, and pre-/post-processing, and 4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of the FAIR principles that extends to computational workflows. Materials Cloud leverages the AiiDA framework to record the provenance of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow to retrace and reproduce any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain. Comment: 19 pages, 8 figure Document type: Article
Abstract
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts [...]
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Intuitive, Interactive Beard and Hair Synthesis with Generative Models
K. Olszewski, J. Echevarria, W. Chen, D. Ceylan, H. Li, Z. Chen, J. Xing

Collection of open conferences in research transport (2020). Vol. 2020, 12

Abstract
We present an interactive approach to synthesizing realistic variations in facial hair in images, ranging from subtle edits to existing hair to the addition of complex and challenging hair in images of clean-shaven subjects. To circumvent the tedious and computationally expensive tasks of modeling, rendering and compositing the 3D geometry of the target hairstyle using the traditional graphics pipeline, we employ a neural network pipeline that synthesizes realistic and detailed images of facial hair directly in the target image in under one second. The synthesis is controlled by simple and sparse guide strokes from the user defining the general structural and color properties of the target hairstyle. We qualitatively and quantitatively evaluate our chosen method compared to several alternative approaches. We show compelling interactive editing results with a prototype user interface that allows novice users to progressively refine the generated image to match their desired hairstyle, and demonstrate that our approach also allows for flexible and high-fidelity scalp hair synthesis. Comment: To be presented in the 2020 Conference on Computer Vision and Pattern Recognition (CVPR 2020, Oral Presentation). Supplementary video can be seen at: https://www.youtube.com/watch?v=v4qOtBATrvM
Abstract
We present an interactive approach to synthesizing realistic variations in facial hair in images, ranging from subtle edits to existing hair to the addition of complex and [...]
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Recruiting Apprentices - The Experience of On-boarding Practices in the Swiss Public Transportation Sector
C. Hämmerli, A. Barabasch

Collection of open conferences in research transport (2020). Vol. 2020, 10

Abstract
The professional socialization in a training company is a great challenge for young people. At the same time, they have to adapt to new organizational structures, integrate into a new workplace and competently master new tasks. Successful vocational socialization depends not only on the interests, abilities, and expectations of the young people but also on the company and its on-boarding practices. The aim of on-boarding measures is to help newcomers to get to know the company's structures and to facilitate their socialization into the culture of the company. Based on findings of an in-depth explorative case study within the public transportation sector in Switzerland, that included interviews with all stakeholders involved in apprenticeship training, the paper will address the practice of on-boarding in apprenticeship training and arrive at conclusions about innovative approaches.
Abstract
The professional socialization in a training company is a great challenge for young people. At the same time, they have to adapt to new organizational structures, integrate [...]
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Extraction and Use of Geometry Data to Obtain 3D Buildings on a Web Map
J. Gómez Pérez, A. Tayebi Tayebi, J. Casado Ballesteros

Collection of open conferences in research transport (2020). Vol. 2020, 9

Abstract
The Fifth International Conference on Advances in Computation, Communications and Services ACCSE 2020, 27/09/2020-01/10/2020, Lisboa, Portugal This work shows a comparison between two different techniques to obtain 3D buildings on a web map. The first one is based on the XYZ Tiles server of OSM Buildings and the second one is based on the Overpass servers of the collaborative project OpenStreetMap. Several simulations have been carried out to analyze their performance. Benefits and limitations of both methods are discussed. Comunidad de Madrid Universidad de Alcalá
Abstract
The Fifth International Conference on Advances in Computation, Communications and Services ACCSE 2020, 27/09/2020-01/10/2020, Lisboa, Portugal This work shows a comparison [...]
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A multi-criteria model for evaluating sustainable transportation system in West Sumatra
L. Berti, E. Amrina

Collection of open conferences in research transport (2020). Vol. 2020, 8

Abstract
Sustainability has become a major concern for transportation planning and policy around the world. This study develops a multi-criteria model to evaluate the sustainable transportation system in West Sumatra. A literature study is carried out to identify the indicators and then validated by the experts. As a result, a total of sixteen indicators divided into six indicators of the economic aspect, five indicators of the social aspect, and five indicators of the environmental aspect are proposed as the indicators of sustainable transportation evaluation. Next, the relationships among the indicators are determined using the Interpretive Structural Modeling (ISM) method. The results show that six indicators consist of accessibility of region, management of public transportation, the infrastructure of public transportation, transportation for people with special needs, level of traffic congestion, and land use to improve transportation facilities identified as the most influencing indicators. On the other hand, passenger convenience is suggested as the most dependent indicator. The importance weight of indicators is then determined using the Analytic Network Process (ANP) method. The land use to improve transportation facilities is regarded as the most important indicator, followed by the level of traffic congestion, and transportation for people with special needs. The model is expected to help the policymaker in improving the performance of a sustainable transportation system.
Abstract
Sustainability has become a major concern for transportation planning and policy around the world. This study develops a multi-criteria model to evaluate the sustainable transportation [...]
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Sustainable Transportation Reform Development through Partnerships Based on Bounded Rationality and Incremental Model
K. Setyowati, D. Suharto, L. Wicaksana

Collection of open conferences in research transport (2020). Vol. 2020, 7
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New Traffic Congestion Analysis Method in Developing Countries (India)
T. Tsuboi

Collection of open conferences in research transport (2020). Vol. 2020, 6
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Consumer Behavior Choice in the Era of Shared Mobility: The Role of Proximity, Competition, and Quality
D. Tong, J. Zhang, W. Cui

Collection of open conferences in research transport (2020). Vol. 2020, 5
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Utilizing Data-Driven Approaches to Evaluate and Develop Air Traffic Controller Action Prediction Models
J. Boo

Collection of open thesis in transport research (2020). Vol. 2020, 81

Abstract
traffic controllers (ATCos) monitor flight operations and resolve predicted aircraft conflicts to ensure safe flights, making them one of the essential human operators in air traffic control systems. Researchers have been studying ATCos with human subjective approaches to understand their tasks and air traffic managing processes. As a result, models were developed to predict ATCo actions. However, there is a gap between our knowledge and the real-world. The developed models have never been validated against the real-world, which creates uncertainties in our understanding of how ATCos detect and resolve predicted aircraft conflicts. Moreover, we do not know how information from air traffic control systems affects their actions. This Ph.D. dissertation work introduces methods to evaluate existing ATCo action prediction models. It develops a prediction model based on flight contextual information (information describing flight operations) to explain the relationship between ATCo actions and information. Unlike conventional approaches, this work takes data-driven approaches that collect large-scale flight tracking data. From the collected real-world data, ATCo actions and corresponding predicted aircraft conflicts were identified by developed algorithms. Comparison methods were developed to measure both qualitative and quantitative differences between solutions from the existing prediction models and ATCo actions on the same aircraft conflicts. The collected data is further utilized to develop an ATCo action prediction model. A hierarchical structure found from analyzing the collected ATCo actions was applied to build a structure for the model. The flight contextual information generated from the collected data was used to predict the actions. Results from this work found that the collected ATCo actions do not show any preferences on the methods to resolve aircraft conflicts. Results found that the evaluated existing prediction model does not reflect the real-world. Also, a large portion of the real conflicts was to be solved by the model both physically and operationally. Lastly, the developed prediction model showed a clear relationship between ATCo actions and applied flight contextual information. These results suggest the following takeaways. First, human actions can be identified from closed-loop data. It could be an alternative approach to collect human subjective data. Second, the importance of evaluating models before implications. Third, potentials to utilize the flight contextual information to conduct high-end prediction models.
Abstract
traffic controllers (ATCos) monitor flight operations and resolve predicted aircraft conflicts to ensure safe flights, making them one of the essential human operators in [...]
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Data-Driven Anomaly and Precursor Detection in Metroplex Airspace Operations
R. Deshmukh

Collection of open thesis in transport research (2020). Vol. 2020, 80

Abstract
div"The air traffic system is one of the most complex and safety-critical systems, which is expected to grow at an average rate of 0.9% a year -- from 51.8 million operational activities in 2018 to 62 million in 2039 -- within the National Airspace System. In such systems, it is important to identify degradations in system performance, especially in terms of safety and efficiency. Among the operations of various subsystems of the air traffic system, the arrival and departure operations in the terminal airspace require more attention because of its higher impact (about 75% incidents) on the entire system's safety, ranging from single aircraft incidents to multi-airport congestion incidents."/div""div""br""/div""div"The first goal of this dissertation is to identify the air traffic system's degradations -- called anomalies -- in the multi-airport terminal airspace or metroplex airspace, by developing anomaly detection models that can separate anomalous flights from normal ones. Within the metroplex airspace, airport operational parameters such as runway configuration and coordination between proximal airports are a major driving factor in aircraft’s behaviors. As a substantial amount of data is continually recording such behaviors through sensing technologies and data collection capabilities, modern machine learning techniques provide powerful tools for the identification of anomalous flights in the metroplex airspace. The proposed algorithm ingests heterogeneous data, comprising the surveillance dataset, which represents an aircraft’s physical behaviors, and the airport operations dataset, which reflects operational procedures at airports. Typically, such aviation data is unlabeled, and thus the proposed algorithm is developed based on hierarchical unsupervised learning approaches for anomaly detection. This base algorithm has been extended to an anomaly monitoring algorithm that uses the developed anomaly detection models to detect anomalous flights within real-time streaming data."/div""div""br""/div""div"A natural next-step after detecting anomalies is to determine the causes for these anomalies. This involves identifying the occurrence of precursors, which are triggers or conditions that precede an anomaly and have some operational correlation to the occurrence of the anomaly. A precursor detection algorithm is developed which learns the causes for the detected anomalies using supervised learning approaches. If detected, the precursor could be used to trigger actions to avoid the anomaly from ever occurring."/div""div""br""/div""div"All proposed algorithms are demonstrated with real air traffic surveillance and operations datasets, comprising of departure and arrival operations at LaGuardia Airport, John F. Kennedy International Airport, and Newark Liberty International Airport, thereby detecting and predicting anomalies for all airborne operations in the terminal airspace within the New York metroplex. Critical insight regarding air traffic management is gained from visualizations and analysis of the results of these extensive tests, which show that the proposed algorithms have a potential to be used as decision-support tools that can aid pilots and air traffic controllers to mitigate anomalies from ever occurring, thus improving the safety and efficiency of metroplex airspace operations."/div
Abstract
div"The air traffic system is one of the most complex and safety-critical systems, which is expected to grow at an average rate of 0.9% a year -- from 51.8 million operational [...]
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Mobility analytics: plan and improve public transportation services though a business intelligence model and dashboards
F. Barnabé

Collection of open thesis in transport research (2020). Vol. 2020, 78

Abstract
Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence Intelligent traffic planning, the promotion of public transport and the improved interconnectedness of all road users in a city-wide communication infrastructure comprise the mobility characteristics of a smart city. Living in an era of Smart Cities emerging, we can make use of all the data available nowadays to better serve our lives with the best services. All the data generated every day by the Vehicles can be used to get a better insights to improve the quality of the available service as the creation of new routes, increase supervision on problematic areas, among others. This document intends to detail the project carried out at Carris, a public transportation company which operates Lisbon's buses, trams, and funiculars. The master thesis project aims to create a Business Intelligence solution to support planning decisions though the use of a Dashboard by presenting information about all relevant data collected on a bus daily route by the driver in order to get a better understating of a public transportation service and how can the organization improve them to rebuild schedules, create or eliminate routes, do some inspection on tickets validations inside the vehicles, etc. This project is supported by a Microsoft tool called Power BI that enables all the extraction, transformation and loading of data processes, based on an Azure SQL Data Warehouse based on Cloud services. The Business Dashboards are divided in 4 main areas inside the organization and will support Onboard Sales, Ticket validations, Route Planning and Onboard issues reported by the driver.
Abstract
Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence [...]
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Evaluation of the efficiency of mainline and ramp metering in highway traffic management
G. Yaran

Collection of open thesis in transport research (2020). Vol. 2020, 74

Abstract
Text in English; Abstract: English and Turkish Includes bibliographical references (leaves 70-72) xi, 72 leaves In the study, the effects of the mainline and ramp control theories on the highway traffic flow are investigate. In order to eliminate to alleviate the traffic congestion problem, which has become a problem in high-population cities, the mainline and ramp controls are considered as a solution, and control networks are emphasized. Examples of applications and results in the world are given. The applicability of the methods to be used by examining the previous studies was first examined on a general model and then on a selected highway network. In the models prepared, vehicle speeds, travel times, flow (volume) concepts, and relationships between them are mentioned. In addition, general information about highway management was also provided before. Control models were examined with the Microscopic Simulation Program, the purpose and types of models applied were compared. The traffic simulation model of the region between K-8 and K-11 on the O-2 highway from Asia to Europe has been created and the effects created by the control have been examined by applying both ramp and mainline metering. Analysis results; It has been observed that the control of ramp and mainline scenarios provides benefits compared to uncontrolled situations. Among the benefits provided; when the analysis of the basic model and mainline metering is applied, it is seen that there is an increase of 20.76% in travel times and an increase of 19.78% in vehicle speeds. Nevertheless, the implications of these control scenarios should be thoroughly investigated. Simulation results show that Ramp Metering (RM) and Mainline Metering (MM) controls can be an effective method in the management of highway-highway connections. In this regard, it is recommended that the control strategies mentioned in intensive highway-to-highway participations be tested in real life in order to increase efficiency. Hazırlanan çalışmada ana yol ve katılım kontrol teorilerinin otoyol trafik akımı üzerindeki etkileri araştırılmıştır. Yüksek nüfuslu şehirlerde bir problem haline gelen trafik tıkanıklığı sorunu, geçiş sırasında oluşan tıkanıklığın ortadan kaldırılması ya da hafifletilmesi amacıyla ana yol ve katılım kontrolleri bir çözüm olarak görülmekte olup kontrol şebekeleri üzerinde durulmuştur. Dünyadaki uygulamalar ve sonuçlarından örnekler verilmiştir. Önceki çalışmalar incelenerek kullanılacak metotların uygulanabilirliği öncelikle genel bir model üzerinde sonrasında da seçilmiş bir otoyol ağı üzerinden uygulanarak incelenmiştir. Hazırlanan modellerde yol ağı ile ilgili araç hızlarına, seyahat sürelerine, akım (hacim) kavramlarına ve aralarındaki ilişkilere değinilmiştir. Ayrıca otoyol yönetimi ile ilgili genel bilgiler de öncesinde sunulmuştur. Kontrol modelleri Mikroskobik Simülasyon Programı ile incelenmiş, amacı, uygulanan model çeşitleri kıyaslamalı olarak anlatılmıştır. Asya Avrupa yönünde O-2 otoyolunda K-8 ile K-11 arasında kalan bölgenin trafik benzetim modeli oluşturulmuş ve hem katılım hem de ana yol kontrolü uygulaması yapılarak, kontrolün yarattığı etkiler incelenmiştir. Analiz sonuçları katılım ve ana yol senaryolarının kontrolünün, kontrolsüz durumlara göre fayda sağladığı görülmüştür. Sağlanan faydalar arasında temel model ve ana yol kontrolünün uygulandığı analizler karşılaştırıldığında; ana yol kontrolünün seyahat sürelerinde % 20,76 kazanç ve araç hızlarında ki % 19,78'lik yükseliş sağladığı görülmektedir. Bununla birlikte, bahsi geçen kontrol senaryoları uygulandığında doğuracağı sonuçlar kapsamlı bir şekilde araştırılmalıdır. Yapılan simülasyon sonuçları katılım (RM) ve anayol (MM) kontrollerinin Otoyol-otoyol bağlantılarının yönetiminde etkili bir yöntem olabileceğini göstermektedir. Bu doğrultuda, verimlilik artışı sağlamak üzere yoğun otoyol-otoyol katılımlarında bahsi geçen kontrol stratejilerinin etkinliğinin gerçek hayatta da sınanması önerilmektedir.
Abstract
Text in English; Abstract: English and Turkish Includes bibliographical references (leaves 70-72) xi, 72 leaves In the study, the effects of the mainline and ramp control [...]
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Long-term prediction using grid based environment models for urban autonomous driving
S. Hörmann

Collection of open thesis in transport research (2020). Vol. 2020, 73
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Urban Design Study for Downtown Taunton, Massachusetts
K. Scanlon

Collection of open thesis in transport research (2020). Vol. 2020, 72

Abstract
This project is an urban design study that encompasses the Downtown area of Taunton, Massachusetts. The boundaries for the study area include the Mill River along the western boundary, Washington Street along the north, Pleasant Street, Leonard Street and Fruit Street along the east, and Church Green and Spring Street along the south boundary. Downtown Taunton is a very well defined and preserved city center that is centered on the Taunton Green and possesses a large number of historic structures. In recent years the downtown has suffered from increasing traffic congestion, the slow destruction of the area' s historic character as modem buildings are constructed on the outskirts of the downtown and in some cases in the downtown itself, and empty storefronts due to a variety of factors. The challenge in completing this study is to develop a plan that will preserve the downtown' s historic character, create a more viable business environment, and create a safer and more attractive environment for pedestrians and motorists. The study is composed of five parts. These include an introduction followed by a short history of the city and downtown area, the structure of city government and a brief profile of the city' s economic and demographic makeup. Part three is an analysis of the downtown to determine assets and liabilities. Part four outlines recommendations to improve the downtown and the last part outlines an implementation strategy to improve the study area functionally and aesthetically. In completing the study the built environment is analyzed to identify the assets and deficiencies of the built environment. In performing this analysis, techniques such as figure/ ground, lynch, and linkage analyses are being used in conjunction with windshield surveys, reviews of existing regulations and studies and interviews with city officials and business owners in the study area. This analysis is then used to develop recommendations to address aspects of the downtown such as zoning, traffic flow, parking, landscaping, street furniture and other amenities, aesthetics, facade treatments, signs and open spaces in an effort to improve the downtown. This study also takes the recommendations one step further by including an implementation strategy that identifies responsible persons, groups, or departments, possible funding sources and assigns a priority to each of the recommendations. The analysis of the study area illustrated the strong base and potential that exists in the downtown in terms of the areas character, layout, architectural beauty, parks, and location. Many of the deficiencies identified are cosmetic in nature although some substantial changes such as traffic flow and the renovation of Court Street are needed. The goal is to provide a built environment that is uniquely and effectively designed, that possesses it own character, is attractive to behold, and convenient and safe to frequent. This creates a sense of place and economic vitality. Downtown Taunton already possesses many of these qualities and the implementation of this plan will move the Downtown closer to fully achieving the above stated goal.
Abstract
This project is an urban design study that encompasses the Downtown area of Taunton, Massachusetts. The boundaries for the study area include the Mill River along the western [...]
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Equity research - Fiat-Chrysler automobiles
M. Oliveira

Collection of open thesis in transport research (2020). Vol. 2020, 71

Abstract
This Equity Research aims at analysing Fiat-Chrysler Automobiles in order to assess the potential capital and dividend gains of holding the stock during 2020. It starts with a brief company description and macroeconomic overview. Afterwards, the automotive sector and its tendencies are analysed. Thereafter, the past performance of each operating segment is summarized to set the context for the valuation. The valuation resorts primarily to the DCF method. Nevertheless, the APV method as well as Multiples are employed to evaluate the results’ accuracy. Finally, a recommendation is, in addition to the associated expected gains and returns with the transaction.
Abstract
This Equity Research aims at analysing Fiat-Chrysler Automobiles in order to assess the potential capital and dividend gains of holding the stock during 2020. It starts with [...]
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Urban logistics in Sao Paulo city: a comparison between Top of the Pyramid and Base of the Pyramid regions
H. Navarro

Collection of open thesis in transport research (2020). Vol. 2020, 68

Abstract
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The fast expansion of urban areas poses challenges for Fast-Moving Consumer Goods (FMCG) companies who want to provide products to small retailers, especially in the last-mile delivery, which is a complex process that is hindered by factors such as transit regulations; city infrastructure; and safety. These factors have different levels of impact, between high-income and low-income neighborhoods and are more evident in megacities in developing countries, where it exists a clear division between classes. On one hand, governments do not attend low-income neighborhoods, where it exists a strong presence of unsafe areas, lack of planning, and infrastructure that hinders the deliveries of FMCG. On the other hand, traffic regulations in high-income neighborhoods make the delivery process more complex. This study aims to analyze the urban logistics by comparing lowincome and high-income neighborhoods in Sao Paulo city, by taking into account local businesses, buying consumer behavior, and the distribution process. To achieve this, a questionnaire in loco will be applied to the stakeholders involved (consumers, small retailers, and carriers). The data will be analyzed by employing descriptive statistics in an exploratory and descriptive way. The results from small retailers, consumers, and carriers reveal that in their point of view the delivery of products is different between BOP and TOP. Factors such as the infrastructure of the neighborhoods hinder the delivery of products from companies to small retailers in TOP regions, while in BOP regions small retailers' security and infrastructure are the major problems in the point of view of the actors. The fast expansion of urban areas poses challenges for Fast-Moving Consumer Goods (FMCG) companies who want to provide products to small retailers, especially in the last-mile delivery, which is a complex process that is hindered by factors such as transit regulations; city infrastructure; and safety. These factors have different levels of impact, between high-income and low-income neighborhoods and are more evident in megacities in developing countries, where it exists a clear division between classes. On one hand, governments do not attend low-income neighborhoods, where it exists a strong presence of unsafe areas, lack of planning, and infrastructure that hinders the deliveries of FMCG. On the other hand, traffic regulations in high-income neighborhoods make the delivery process more complex. This study aims to analyze the urban logistics by comparing lowincome and high-income neighborhoods in Sao Paulo city, by taking into account local businesses, buying consumer behavior, and the distribution process. To achieve this, a questionnaire in loco will be applied to the stakeholders involved (consumers, small retailers, and carriers). The data will be analyzed by employing descriptive statistics in an exploratory and descriptive way. The results from small retailers, consumers, and carriers reveal that in their point of view the delivery of products is different between BOP and TOP. Factors such as the infrastructure of the neighborhoods hinder the delivery of products from companies to small retailers in TOP regions, while in BOP regions small retailers' security and infrastructure are the major problems in the point of view of the actors. CNPJ00.394.445/0191-12
Abstract
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The fast expansion of urban areas poses challenges for Fast-Moving Consumer Goods (FMCG) companies [...]
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The potential impact of ride-hailing services on BYD
I. Shapovalova

Collection of open thesis in transport research (2020). Vol. 2020, 67

Abstract
Shared mobility, including ride-hailing services, has been on the rise, enabled by emerging technologies, and allowing for more convenient and flexible travel. The Chinese market is particularly attractive for ride-hailing as the country pushes to relieve its transportation problems, namely traffic congestion and subjacent economic implications. This study aims to measure the impact of ride-hailing services on BYD’s share price performance. Three different scenarios of disruption were analyzed, quantifying the potential decrease in revenues. Moreover, an alternative view was considered, taking into consideration the depreciation suffered by society as a whole and the rate of substitution of vehicles.
Abstract
Shared mobility, including ride-hailing services, has been on the rise, enabled by emerging technologies, and allowing for more convenient and flexible [...]
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Innovation Adaptation in Urban Light-Rail Transport: Adapting Pricing and Infrastructural Innovations using Frugal Approach in Ethiopia and Nigeria: Innovatie en aanpassing in stedelijk light-rail vervoer: Aanpassing van beprijzing- en infrastructuurinnovaties met behulp van een sobere aanpak in Ethiopië en Nigeria
T. Alade

Collection of open thesis in transport research (2020). Vol. 2020, 66
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Driving solar : Integrating photovoltaic systems, electric vehicles, and consumer behaviour in models of smart energy systems
M. Kam

Collection of open thesis in transport research (2020). Vol. 2020, 65

Abstract
Large-scale adoption of clean energy technologies, such as photovoltaic (PV) solar panels and electric vehicles (EVs), is key for ensuring a sustainable future. However, integrating clean energy technologies in the existing electricity grid is challenging for grid management. Aligning EV charging demand with PV power production via smart charging or using EVs as electricity storage in vehicle-to-grid (V2G) systems can reduce the impact of both technologies on the grid. Realizing the potential of such systems requires consumers to adopt these technologies, shift EV charging demand, and allow for discharging of EVs; a radical change from current energy behaviours. The extent to which consumers will do so is a major source of uncertainty in assessing the future of sustainable energy systems. This thesis analyses and qualifies this uncertainty by developing simulation models that incorporate technical as well as social aspects of smart charging and V2G. This multi-disciplinary approach allows to study how consumer behaviour could shape sustainable energy systems. Furthermore, the thesis analyses large datasets on actual diffusion and use of PV solar panels and EVs in the Netherlands. The results show that there can be great benefits for grid management in combining intermittent renewable energy sources with EVs via smart and/or V2G. However, this can only be a partial solution for load balancing in scenarios with high renewable energy uptake. Furthermore, consumer adoption and charging behaviour varies greatly, which influences the extent to which the envisioned benefits of smart charging and V2G can be realized in certain regions and neighbourhoods.
Abstract
Large-scale adoption of clean energy technologies, such as photovoltaic (PV) solar panels and electric vehicles (EVs), is key for ensuring a sustainable future. However, integrating [...]
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Impact of traffic incident duration and road characteristics on traffic flow performance
A. Alan

Collection of open thesis in transport research (2020). Vol. 2020, 64

Abstract
Text in English; Abstract: English and Turkish Includes bibliographical references (leaves 207-214) xx, 230 leaves Non-recurrent events that occur in any part of the highway such as accident, vehicle breakdown,fire, scattering of substances like load, fuel oil etc. on the road which disrupt the traffic flow are defined as traffic incidents. Traffic Incident Management is the planned and coordinated utilization of all human and institutional resources in order to reduce the negative effects of these incidents and to ensure the safety of the drivers, pedestrians, all other victims and response teams. Incidents generally causes congestion and yields in increased travel time which imposes costs to road users, either economic loss or reduced quality of life and mobility. This thesis presents the recent literature review on the traffic incident management theory and practice along with the traffic incident simulation models. The thesis study is comprised of two parts; a data collection and analysis and a simulation experiment phase. Firstly, Traffic incident data from Istanbul Metropolitan Area is collected and analyzed. Secondly, a microscopic traffic simulation model was developed to simulate different types of incidents and traffic demand and also various geometric characteristics of highway. The analyses are performed taking total travel time, queue length and the speed as performance measures. Lastly, to evaluate and compare the performance of the cases, statistical tests are applied. The results show that there is a linear relationship between the incident duration and the average flow speed. The increase in incident duration causes the decrease in average speed up to 11.8% for overall traffic flow and up to 29.6% for the traffic flow of the post-incident process. The longest average queue length is observed in incidents in the middle lane. The shortest average queue length is observed in incidents in the right lane. In incidents in the middle lane, queue length increases up to 34.6% compared to the incidents in the right lane for overall traffic flow. In cases where the number of vehicles per lane is the same, the increase in the number of lanes causes a decrease in average speed up to 6.4% for the traffic flow of the post-incident process. According to the results of the applied statistical tests, when overall simulation periods are analyzed, statistically different results are seen only in incident duration, vehicle input, and lane width changes. When post-incident processes are analyzed, statistically different results are seen only in incident duration and lane width changes. The results of this thesis could be used by the traffic control authorities to reduce incident duration, congestion, secondary incidents, and the associated human and economic losses. Karayolunun herhangi bir kesiminde meydana gelen kaza, araç arızası, yangın, yük, akaryakıt vb. maddelerin yola saçılması gibi trafik akımını bozan tekrarsız durumlar trafik olayları olarak tanımlanır. Trafik Olay Yönetimi, bu olayların olumsuz etkilerini azaltmak; sürücülerin, yayaların, diğer tüm mağdurların ve müdahale ekiplerinin can güvenliğini sağlamak için insani ve kurumsal bütün kaynakların planlı ve koordineli bir biçimde kullanılmasıdır. Olaylar genellikle yol kullanıcılarına, ekonomik kayıp veya düşük yaşam kalitesi ve hareket kabiliyeti gibi maliyetler getiren seyahat süresinde artışa neden olan tıkanıklığa sebep olurlar. Bu tez, trafik olayı simülasyon modelleri ile birlikte trafik olay yönetimi teorisi ve uygulaması hakkındaki güncel literatür incelemesini sunmaktadır. Tez çalışması; veri toplama ve analizi ile simülasyon deney aşaması olmak üzere iki bölümden oluşmaktadır. İlk olarak, İstanbul Büyükşehir Belediyesi sınırları içinden trafik olayı verileri toplanmış ve analiz edilmiştir. İkinci olarak, farklı olay türlerini ve trafik talebini ve ayrıca karayolunun çeşitli geometrik özelliklerini simüle etmek için mikroskobik bir trafik simülasyon modeli geliştirilmiştir. Analizler performans ölçütü olarak toplam seyahat süresi, kuyruk uzunluğu ve hız dikkate alınarak yapılmıştır. Son olarak, bu durumların performansını değerlendirmek ve karşılaştırmak için istatistiksel testler uygulanmıştır. Tez sonuçları göstermektedir ki olay süresi ile ortalama akım hızı arasında lineer bir ilişki vardır. Olay süresindeki artış ortalama hızda genel trafik akımı için %11.8'e varan, olay sonrası sürecin trafik akımı içinse %29.6'ya varan azalmaya sebep olmaktadır. En uzun ortalama kuyruk boyu orta şeritte meydana gelen olaylarda gözlemlenmektedir. En kısa ortalama kuyruk boyu sağ şeritte meydana gelen olaylarda gözlemlenmektedir. Genel trafik akımı için orta şeritte meydana gelen olaylarda sağ şeritte meydana gelen olaylara kıyasla kuyruk boyu %34.6'ya kadar artmaktadır. Şerit başına düşen araç sayısının aynı olduğu durumlarda, şerit sayısındaki artış, olay sonrası sürecin trafik akımı için ortalama hızda %6.4'e varan bir azalmaya neden olmaktadır. Uygulanan istatistiksel testlerin sonuçlarına göre, genel simülasyon periyotları incelendiğinde, istatistiksel olarak farklı sonuçlar sadece olay süresi, araç girdisi ve şerit genişliği değişikliklerinde görülmüştür. Kaza sonrası süreçler incelendiğinde ise, sadece olay süresi ve şerit genişliği değişimlerinde istatistiksel olarak farklı sonuçlar görülmüştür. Bu tezin sonuçları trafik kontrol yetkilileri tarafından olay süresini, tıkanıklığı, ikincil olayları ve ilgili insani ve ekonomik kayıpları azaltmak için kullanılabilir.
Abstract
Text in English; Abstract: English and Turkish Includes bibliographical references (leaves 207-214) xx, 230 leaves Non-recurrent events that occur in any part of the highway [...]
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Apoio à Decisão para o Planeamento de uma Infraestrutura de Carregamento de um sistema de Autocarro de Trânsito Rápido
J. Manzolli

Collection of open thesis in transport research (2020). Vol. 2020, 63

Abstract
Dissertação de Mestrado em Energia para a Sustentabilidade apresentada à Faculdade de Ciências e Tecnologia Atualmente, uma das maiores preocupações mundiais é a mudança climática e seus efeitos irreversíveis no equilíbrio dos ecossistemas da Terra. Portanto, várias instituições, organizações e governos estão desenvolvendo políticas, medidas e tecnologias para mitigar esses efeitos. Nesse contexto, a eletrificação dos sistemas de transporte público desempenha um papel decisivo em termos de atenuação das emissões de gases de efeito estufa. Além disso, os veículos elétricos possuem muitas vantagens quando comparados aos seus equivalentes de combustíveis fósseis, incluindo melhoria da qualidade do ar, redução de ruído e melhoria da eficiência energética. Apesar desses benefícios, os veículos elétricos ainda sofrem com a baixa autonomia e recargas demoradas da bateria. Para fornecer soluções para esses problemas e aumentar a viabilidade da mobilidade elétrica, o desenvolvimento de tecnologias nas infraestruturas de carregamento, métodos de controle e capacidade de baterias torna-se crucial. Neste contexto, a presente pesquisa fornece uma abordagem para o planejamento da infraestrutura de carregamento de um sistema de Autocarro de Trânsito Rápido (BRT), que trata da minimização dos custos de implementação das estações de carregamento rápido. O trabalho apresenta inicialmente um estudo de Análise de Decisão Multicritérios afim de avaliar quais tipos de sistemas de trânsito rápido podem oferecer uma solução mais conveniente em áreas metropolitanas. O principal objetivo desta análise é avaliar se um sistema de BRT pode ser uma solução viável para esse fim, quando comparado a outros sistemas de trânsito rápido. Em seguida, um modelo de Programação Linear Inteira Mista é desenvolvido para otimizar a localização das estações de carregamento rápido em uma rede BRT, considerando o custo de implementação, número de carregadores, tempo total de carregamento e ciclo de vida da bateria. Nowadays, one of the biggest concerns worldwide is Climate Change and its irreversible effects on the balance of the Earth's ecosystems. Therefore, several institutions, organizations, and governments are developing policies, measures, and technologies to mitigate such effects. In this context, the electrification of public transportation systems plays a decisive role in greenhouse gas emissions attenuation. Moreover, electric vehicles have many advantages when compared to their fossil fuel counterparts, including air quality improvement, noise reduction, and energy efficiency enhancement. Despite those benefits, electric vehicles still suffer from the low driving range, and the time-consuming battery recharges. To provide solutions to those issues and to increase the feasibility of electric mobility, the development of technologies in charging infrastructures, control methods, and battery capacity becomes crucial. In this context, the present research provides a framework for the planning of the charging infrastructure of a Bus Rapid Transit (BRT) system dealing with the minimization of the implementation costs of fast-charging stations. The work initially presents a Multi-criteria Decision Analysis study to assess which types of rapid transit systems can offer a more convenient solution for metropolitan areas. The main objective of this analysis is to evaluate whether a BRT system can be a viable solution for this purpose when compared to other rapid transit systems. Then a Mixed Integer Linear Programming model is developed to optimize the location of fast-charging stations in a BRT network, considering the cost of implementation, number of chargers, total charging time, and battery life cycle.
Abstract
Dissertação de Mestrado em Energia para a Sustentabilidade apresentada à Faculdade de Ciências e Tecnologia Atualmente, uma das maiores preocupações mundiais é a mudança [...]
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Bus performance enhancement by means of the of traffic light control optimization
P. Arrom Coll

Collection of open thesis in transport research (2020). Vol. 2020, 59
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Miljøpåvirkninger fra produksjon og bruk av hydrogen i maritim transport
S. Myhre

Collection of open thesis in transport research (2020). Vol. 2020, 58

Abstract
I denne studien er hydrogen foreslått som et alternativt drivstoff for maritim transport. Miljøpåvirkninger fra å erstatte konvensjonelle fossile brensler i sjøtransport med hydrogen vurderes ved å utføre en livssyklusvurdering av hele transportlivssyklusen. Systemet dekker påvirkninger knyttet til både infrastruktur, fartøy og drivstoff. Bare fullstendige referanser av fyringsoljer, flytende naturgass og hydrogen har vært mulig å oppdrive og begrenser derfor studiet. Batterier blir også vurdert, men bare som en ekstra kraftgenererende enhet i hybridsystemer, da de har en mangel på energi per vektenhet sammenlignet med andre drivstoff. LCAen som er gjennomført i denne studien involverer flere påvirkningskategorier inkludert: forsuring, abiotisk uttømming (av fossilt brensel), overgjødsling, økotoksisitet (gjelder både ferskvann, sjø og land), globalt oppvarmingspotensial, menneskelig toksisitet, nedbryting av ozonlag og fotokjemisk oksidasjon. Energibruk for de forskjellige drivstoffene blir undersøkt ved beregning av kumulativt energibehov. Som resultatene antyder, kan erstatning av deler av den nåværende drivstoffblandingen i sjøtransport med hydrogen føre til en betydelig mindre innvirkning på miljøet. Nytten av å bruke hydrogen i sjøtransport er imidlertid sterkt avhengig av tilgangen til et rent drivstoff. Siden produksjonsnivåene er lave i tillegg til sikkerhetsrisikoer for bruk av hydrogen ombord på skip, er det nødvendig å fortsette å utvikle hydrogenteknologien på både en kostnadseffektiv og energieffektiv måte for å konkurrere med velutviklede teknologier. Masteroppgave i energi ENERGI399 MAMN-ENERG
Abstract
I denne studien er hydrogen foreslått som et alternativt drivstoff for maritim transport. Miljøpåvirkninger fra å erstatte konvensjonelle fossile brensler i sjøtransport [...]
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Simulation and optimization of a multi-agent system on physical internet enabled interconnected urban logistics.
L. Zheng

Collection of open thesis in transport research (2020). Vol. 2020, 57
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DESIGNING EFFECTIVE MESSAGES FOR INCREASING READINESS TO USE ALTERNATIVE TRANSPORTATION
J. Drew

Collection of open thesis in transport research (2020). Vol. 2020, 53

Abstract
The use of single-occupancy vehicles (SOVs) has had a profound impact on human health and the environment. In order to change the impact our travel behavior has on both the environment and our health, change needs to occur at an individual level. The purpose of this study was to determine effective framing strategies that will encourage individuals to use alternative, or sustainable transportation (ST), i.e. commuting by means other than SOV, and to compare the efficacy of this intervention to that of a “green” eating (GE) intervention. Using the Transtheoretical model (TTM) and its key constructs, self-efficacy and decisional balance, data were collected from 134 undergraduate students at the University of Rhode Island measuring their attitudes towards ST and GE, respectively. The intervention consisted of a pretest survey, four educational modules, tailored messaging and finally, a posttest. Data from the pretest survey contained each participant’s Stage of Change reflecting attitudes toward ST and GE. After the pretest, participants were randomized into the GE group or the ST group. Participants in the GE and ST groups received educational modules over the course of three weeks. Between each educational module, participants received motivational messages tailored to their respective stage, as determined in the pretest. Results from tests revealed that there were small positive shifts in stages in each of the treatment groups as well as small increases in decisional balance and self-efficacy as a result of the ST intervention.
Abstract
The use of single-occupancy vehicles (SOVs) has had a profound impact on human health and the environment. In order to change the impact our travel behavior has on both the [...]
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What´s the extra mile for consumers´ adoption of electric vehicles? : a netnographic study on electric vehicles online communities
F. Pereira

Collection of open thesis in transport research (2020). Vol. 2020, 52

Abstract
The progress of the global agenda for sustainable development, as well as increased concerns over climate change and global resource storage, are in the centre of this century discussions and concerns. Such concerns foster the demand for electric vehicles as these contribute to a more sustainable transportation system by reducing greenhouse gas emissions. The present dissertation aims to study online communities of electric vehicles enthusiasts, understanding their attitudes, behaviours and opinions towards electric vehicles purchase intentions. Hence, netnography is considered the most appropriate qualitative research method to conduct this research. Results demonstrate that electric vehicles purchase intentions are affected by the consumers weighting of drivers, barriers, and mostly, perceived self-image. Further, this research shows that purchase intentions of electric vehicles are highly motivated by social influence. This study contributes to current academic discussion on the influential factors of this technology diffusion, unveiling interesting findings regarding the pre-eminence of perceived self-image and vehicle performance over environmental concerns, on purchase intentions. The desired change of behaviours and attitudes towards a more sustainable lifestyle, should be enticed at a societal level through Social Marketing. Governments should promote a more sustainable behaviour on the transportation paradigm by investing in the development of charging infrastructures and promoting the adoption of electric vehicles through stricter policies and incentives. Conspicuously, companies should leverage on governments actions and policies by advocating the futuristic and innovative technology, enhancing consumers perceived self-image to hasten electric vehicles diffusion O progresso da agenda global para o desenvolvimento sustentável e o armazenamento de recursos globais, estão no centro das discussões e preocupações deste século. Estas preocupações estão a fomentar a procura de veículos elétricos, uma vez que estes favorecem a redução de emissões de gases com efeito estufa e contribuem para um sistema de transporte mais sustentável. A presente dissertação visa, por isso, analisar comunidades online de entusiastas de veículos elétricos e compreender as suas atitudes, comportamentos e opiniões em relação às intenções de compra de veículos elétricos. Deste modo, netnografia é considerado o método de investigação qualitativo mais adequado para esta investigação. Os resultados demonstram que as intenções de compra de veículos elétricos são afetadas pela forma como os consumidores avaliam motivações, barreiras e percecionam autoimagem. Adicionalmente, as intenções de compra são fortemente motivadas pela influência social. Este estudo contribui para a atual discussão académica sobre os fatores influentes na difusão desta tecnologia, revelando a preeminência da perceção da autoimagem e do desempenho dos veículos em detrimento de preocupações ambientais na intenção de compra. A desejada mudança de comportamentos e atitudes para um estilo de vida mais sustentável deve ser fomentada através do Marketing Social. Os governos devem promover um comportamento mais sustentável no sistema de transporte, promovendo a adoção de veículos elétricos e investindo no desenvolvimento de infraestruturas de carregamento. Seguidamente, as empresas devem aproveitar as ações e políticas dos governos, promovendo tecnologia futurista e inovadora, potenciando a autoimagem dos consumidores para acelerar a difusão de veículos elétricos.
Abstract
The progress of the global agenda for sustainable development, as well as increased concerns over climate change and global resource storage, are in the centre of this century [...]
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REGIONAL TRANSPORTATION PLANNING IN SOUTHEASTERN CONNECTICUT: AN ASSESSMENT OF THE MAC
H. Samokar

Collection of open thesis in transport research (2020). Vol. 2020, 51

Abstract
This project analyzed a regional transportation planning process in Southeastern Connecticut. For two years, the Multi-Modal Advisory Committee (known as the MAC) met, under the direction of a transportation consultant and a facilitator, to address the region ' s traffic congestion. Specifically, their efforts comprised a Major Investment Study (MIS) which is a predecessor to an Environmental Impact Statement (EIS). The MAC's goal was to reach consensus on which transportation alternatives the consultant should further study in the EIS. This group did not reach consensus. The study looked at two types of factors that may have affected the outcome of the MAC: internal factors and external factors. Internal factors are those which occurred during the process. This entailed an analysis of the groups' common understanding of the problem and objectives, the groups' defined expectations, member' s participation, and the role of the project team. The study found that the MAC lacked agreement on the problem at hand and on many aspects of the process. Additionally , the facilitator and project team did not appear to respond accordingly to address these problems. To assess the effects of external factors , the study analyzed the history of regional cooperation in the study area, regional capacity, power, local politics, and public influence on the process. The findings indicated that a lack of power and funding discouraged the members of the MAC. Also, the group could not separate other problems in the region from the process. The project concludes with recommendations for Southeastern Connecticut and future transportation planning processes. More time should be spent on clarifying the details during the process, such as definitions, evaluation criteria, and the scope of
Abstract
This project analyzed a regional transportation planning process in Southeastern Connecticut. For two years, the Multi-Modal Advisory Committee (known as the MAC) met, under [...]
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Selection factors for behavioral intention regarding electric vehicles in Norway
V. Hussein, E. Sværen

Collection of open thesis in transport research (2020). Vol. 2020, 50

Abstract
Master's thesis in Economics Norway has acted as a laboratory for electric vehicles. It has taken a leading role in the introduction of electric vehicles and the development of a sustainable electric vehicle market. According to a recent report from the Norwegian Electric Vehicles Association (NEVA), electric vehicles in Norway have enjoyed increasing sales of almost one-third per year. Given this staggering rise, the purpose of this study is to identify the variables that impact people’s intent on electric vehicle adoption in Norway. An online survey is conducted to determine the selection factors for the behavioral intentions of 280 individuals towards electric vehicles in Norway. Applying multiple regression analysis, the study finds that environmental concern, subjective norms, reception of economic benefits, and overall perception of electric vehicles have a statistically significant influence on people’s behavioral intention to buy an electric vehicle. The regression analysis concludes that the direct effect of the reception of economic benefit (β = 0.309) is more significant than the direct effect of subjective norms (β = 0.291) and the perception of electric vehicles (β = 0.241). Our findings provide a better understanding of Norwegian consumers’ motivations in buying electric vehicles and should guide the government, electric vehicle manufacturers, and investors in Norway to better marketing and incentivization decisions.
Abstract
Master's thesis in Economics Norway has acted as a laboratory for electric vehicles. It has taken a leading role in the introduction of electric vehicles and the development [...]
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A STUDY OF U.S. ROUTE 17-92 CORRIDOR, ORANGE CITY, FLORIDA
E. Pimentel

Collection of open thesis in transport research (2020). Vol. 2020, 49

Abstract
The City of Orange City, Florida is located approximately midway between Daytona Beach and Orlando, Florida. Therefore, it is directly situated in the mecca of Florida tourism. Orange City has had a long and rich history, including the st, Johns and Blue Springs which were the site of more Civil War battles than any other locality as well as having contained one of the most nationally renowned natural springs. In fact, Orange City once contained one of the largest orange groves. However, population surges in the City as well as surrounding Communities over the past forty years, has contributed to vast commercial development, and in turn greater automobile usage. This has resulted in increased highway travel, thereby impacting the primary highway traversing Orange City, namely us Route 17-92. The purpose of this study is to define precisely what the problems were affecting us Route 17-92, and in turn the quality of life in Orange City. An assessment of these problems were obtained through various sources, including discussions with Orange City and Volusia County staff. However, great insight was acquired from Orange City residents and business owners located along us Route 17-92, by means of two surveys. Information was obtained from Orange City residents through a telephone survey, and procured from businesses located on us Route 17-92 through a personally hand-delivered survey. From the findings of the above analysis, the following problems were identified; traffic congestion, high number of accidents, deteriorated City and County streets, unfriendly pedestrian environment and limited pedestrian amenities, as well as an unattractive appearance. The last problem included limited landscaping, vast unbuffered frontage oriented parking lots, haphazard commercial signage and unappealing City signage. After identifying these problems, the study formulated recommendations using the results of both the resident and business owners surveys. Three categories of recommendations were devised. First, recommendations to reduce the existing highway hazards. Second, recommendations to establish a pedestrian-friendly environment. Lastly, recommendations to address the aesthetics of the project area.
Abstract
The City of Orange City, Florida is located approximately midway between Daytona Beach and Orlando, Florida. Therefore, it is directly situated in the mecca of Florida tourism. [...]
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The impact of Thailand's high-speed railways (HSR) development plan on overnight stays in a tourism promotional city
H. Boonporn

Collection of open thesis in transport research (2020). Vol. 2020, 48
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DEVELOPMENT OF A SUSTAINABLE TRANSPORTATION INFRASTRUCTURE MANAGEMENT SYSTEM FOR A TYPICAL COLLEGE CAMPUS
A. Singh

Collection of open thesis in transport research (2020). Vol. 2020, 46
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Raisonnement sémantique pour une plateforme d’assistance intelligente orienté bien-être et santé numérique
M. Kodys

Collection of open thesis in transport research (2020). Vol. 2020, 44

Abstract
Connected objects of everyday living have made their way into our lives. Known as Internet of Things, the various technologies inspire a vast variety of applications. One of the pioneer applications is the concept and development of a smart home. This is now spreading outdoors; making vehicles, buildings, and even large cities smart. Moreover, the technology is getting more personal as well – as wearing smart clothes and other self-tracking devices become increasingly common and popular. This is often referred to as the quantified self.One particular case of a smart environment is ambient assisted living, which is designed to enhance elderly people’s day-to-day life. Such a ubiquitous and unobtrusive computer system can also be ported to other domains and age groups. For instance, the tracking of daily activities can also help younger adults to improve their lifestyle. Everyone can be encouraged to maintain a healthy lifestyle, perform sufficient physical activity, and make more informed decisions about their mobility. These are direct factors in preventing health risks, such as metabolic diseases like the type 2 diabetes, and allow a better control over respiratory diseases like the asthma.Driven by these ideas, this thesis explores the possibilities of a web-based platform with a semantic rule-based reasoning. The thesis details the work on technical improvements, enhancements in activity recognition, extensions for data analysis, and a mobility-oriented application.Following a user-centric approach, a real life deployment of the described technologies is necessary. Two use cases are examined. First, I enhanced and built upon a pre-existing system, which consists of sensors and a gateway placed into elderly participants' homes. The second use case is the deployment of a mobile phone application for active mobility assistance. Collecting relevant and timely data, the application then outputs a level of recommendation for every type of mobility. The recommendations are based on each user’s exercise tracking device, which incorporates their goals, their profiles, and other publicly available data sources such as weather and air quality.This thesis describes the outcomes and lessons learnt from these deployments. In addition, this thesis provides an in-depth discussion as well as analytical insights on the results of the deployments.; Les objets connectés de la vie courante ont trouvé leur chemin dans notre quotidien. Connu sous le terme d'Internet des choses, une pluralité de technologies inspire une vaste variété des cas d'utilisation. Une des applications innovatrices est le concept et le développement de la maison intelligente. Actuellement, ce concept est en train de s'étendre vers l'extérieur ; il rend futés des véhicules, bâtiments et même des villes entières. De plus, la technologie devient aussi plus personnelle - comme le port des vêtements futés et d'autres appareils pour l'autosurveillance personnelle devient de plus en plus courant et populaire. Ce phénomène est souvent appelée le soi quantifié.Un cas particulier de l'environnement futé est l'assistance à l'autonomie à domicile (ambient assisted living) conçue pour améliorer la qualité de la vie quotidienne des personnes âgées. Un tel système informatique, omniprésent et discret, peut être porté dans d'autres domaines et tranches d'âge. Par exemple, le suivi des activités du quotidien peut aider jeune adultes à améliorer leur mode de vie. Tout le monde peut être encouragé à maintenir un mode de vie sain, à exercer une activité physique suffisante et prendre les décisions fondées quant à la mobilité. Ce sont les facteurs direct contribuant à la prévention des risques de santé, tel que les maladies métaboliques comme le diabète de type 2 ; et permettent un meilleur maîtrise des maladies respiratoires comme l'asthme.Dirigée par ces idées, cette thèse explore les possibilités d'une plate-forme web avec un raisonnement sémantique basé sur les règles. La thèse détaille le travail sur les améliorations techniques, avancements dans la reconnaissance d'activités, les extensions pour l'analyse des données et une application orientée mobilité.Suivant l'approche centrée utilisateur, un déploiement dans les conditions réelles est necessary. Deux cas d'utilisation sont abordés. Le premier est l'amélioration du système existant, consistant des capteurs et d'une passerelle tous placés dans le domicile de la personne âgée. Le deuxième cas est le déploiement d'une application pour téléphones portables pour l'assistance à la mobilité active. En collectant les donnés relevantes et actuelles, l'application affiche un niveau de recommandation personnalisée pour chaque type de mobilité. Ces recommandations sont basées sur l'appareil de soi quantifié qui incorpore les objectifs personnels, le profil et autres données librement accessible, tel que la météo ou la qualité d'air.Cette thèse décrit les sorties et les leçons tirées des déploiements de ces technologies. Cette thèse apporte une discussion et des analyses des résultats de ces déploiements.
Abstract
Connected objects of everyday living have made their way into our lives. Known as Internet of Things, the various technologies inspire a vast variety of applications. One [...]
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Advantages of pre-cast concrete in airport construction
K. Kuparowitzová

Collection of open thesis in transport research (2020). Vol. 2020, 43

Abstract
refabrication in infrastructural development with a focus on airport construction and its necessity for the project's short duration. The technology of precast panels is explained in the first part of the thesis including the specifics of different areas (structures) of the airports and their various needs. A comparison between precast and cast-in-place methods is performed regarding the construction time and financial aspects. Case study of the planned expansion and a hypothetical reconstruction at the Barcelona El Prat airport is analyzed and consequent conclusions and recommendations are made. Incoming
Abstract
refabrication in infrastructural development with a focus on airport construction and its necessity for the project's short duration. The technology of precast panels is explained [...]
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User Acceptance of Automated Vehicles in Public Transport
S. Nordhoff

Collection of open thesis in transport research (2020). Vol. 2020, 42

Abstract
The acceptance of automated vehicles is a necessary condition for realizing the benefits of road vehicle automation. The objective of the thesis was to examine the acceptance of automated vehicles feeding public transport. The thesis investigated the factors contributing to user acceptance, as well as the interrelations of those factors. It was also investigated how acceptance differs across socio-demographic groups and countries. Online questionnaires, semi-structured interviews, a systematic literature review, and accompanied test rides were performed. Participants were asked to imagine the use of automated vehicles (Chapter 2) or physically experienced them in mixed traffic environments in Berlin (Germany) and Trikala (Greece) (Chapters 3–5, 7–8)....
Abstract
The acceptance of automated vehicles is a necessary condition for realizing the benefits of road vehicle automation. The objective of the thesis was to examine the acceptance [...]
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Méthodes d'optimisation basée sur la simulation pour le covoiturage dynamique
N. ALISOLTANI DEHKORDI

Collection of open thesis in transport research (2020). Vol. 2020, 41

Abstract
The main goal of this dissertation is to answer one of the critical questions about dynamic ride-sharing services: Can dynamic ride-sharing reduce congestion? In this thesis, we propose a simulation-based optimization framework for dynamic ridesharing. Then using this framework, we assess the dynamic ride-sharing impact on two different network scales to find the answer to this question. When assessing the dynamic ride-sharing problem, two important points should be considered. First, how the ridesharing system serves the network demand and second, how the ride-sharing system is impacted by the network and in particular by congestion. Then we can assess the impact of such a service on the network. Most of the existing approaches focus on the first point, i.e., designing the demand matching while using basic assumptions for the second point, mainly constant travel times. The proposed method in this thesis can outperform the existing methods in the literature. The optimization algorithm can provide high-quality solutions in a short time. Our solution approach is designed to be exact for small samples. Then, to be able to handle the large-scale problems, it is extended with several heuristics that keep the general design for the solution method but significantly reduce its computation time. In the simulation component, a "Plant Model" is applied based on the "Trip-based Macroscopic Fundamental Diagram (MFD)" to represent the traffic dynamics reality and a "Prediction Model" is applied based on the mean-speed to be used during the assignment process. We perform an extensive simulation study (based on real-world traffic patterns) to assess the influence of dynamic ride-sharing systems on traffic congestion. In the medium-scale (Lyon 6 + Villeurbanne), the results showed that ride-sharing could not significantly improve the traffic situation. High levels of market-share add additional travel distance and travel time to the trips and lead to more traffic in the network. In large cities, the results are entirely different from those in small and medium-sized cities. In large-scale (Lyon city in France) simulations, the proposed dynamic ride-sharing system can significantly improve traffic conditions, especially during peak hours. Increasing the market-share and the number of sharing can enhance this improvement. Therefore, the proposed dynamic ride-sharing system is a viable option, alleviating stress on existing public transport, to reduce the network traffic in populated and large-scale cities.; The main goal of this dissertation is to answer one of the critical questions about dynamic ride-sharing services: Can dynamic ride-sharing reduce congestion? In this thesis, we propose a simulation-based optimization framework for dynamic ridesharing. Then using this framework, we assess the dynamic ride-sharing impact on two different network scales to find the answer to this question. When assessing the dynamic ride-sharing problem, two important points should be considered. First, how the ridesharing system serves the network demand and second, how the ride-sharing system is impacted by the network and in particular by congestion. Then we can assess the impact of such a service on the network. Most of the existing approaches focus on the first point, i.e., designing the demand matching while using basic assumptions for the second point, mainly constant travel times. The proposed method in this thesis can outperform the existing methods in the literature. The optimization algorithm can provide high-quality solutions in a short time. Our solution approach is designed to be exact for small samples. Then, to be able to handle the large-scale problems, it is extended with several heuristics that keep the general design for the solution method but significantly reduce its computation time. In the simulation component, a "Plant Model" is applied based on the "Trip-based Macroscopic Fundamental Diagram (MFD)" to represent the traffic dynamics reality and a "Prediction Model" is applied based on the mean-speed to be used during the assignment process. We perform an extensive simulation study (based on real-world traffic patterns) to assess the influence of dynamic ride-sharing systems on traffic congestion. In the medium-scale (Lyon 6 + Villeurbanne), the results showed that ride-sharing could not significantly improve the traffic situation. High levels of market-share add additional travel distance and travel time to the trips and lead to more traffic in the network. In large cities, the results are entirely different from those in small and medium-sized cities. In large-scale (Lyon city in France) simulations, the proposed dynamic ride-sharing system can significantly improve traffic conditions, especially during peak hours. Increasing the market-share and the number of sharing can enhance this improvement. Therefore, the proposed dynamic ride-sharing system is a viable option, alleviating stress on existing public transport, to reduce the network traffic in populated and large-scale cities.
Abstract
The main goal of this dissertation is to answer one of the critical questions about dynamic ride-sharing services: Can dynamic ride-sharing reduce congestion? In this thesis, [...]
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Parking management in smart built environment: Evaluation of METU Campus
V. Genel

Collection of open thesis in transport research (2020). Vol. 2020, 40

Abstract
With the ever-increasing number of vehicles and technological advancements, transportation-related social problems are addressed with more systematic and smarter solutions, as a part of Intelligent Transportation Systems (ITS) services. Parking management is an ITS application area, where limited parking capacities can be efficiently and fairly utilized by more road users. However, detection of the true nature of parking demand and supply limits as well as the expected response to any policies and technology tools to be employed, is necessary prerequisite step. Middle East Technical University (METU) campus is a built environment that suffers from parking-related problems due to limited parking supply capacity despite the increase in the demand. Thus, parking violations have been increasing lately due to high number of cars in the campus. Besides the negative environmental impacts, parking violations have started to threaten the flow and safety of the campus traffic due to traffic congestion and loss of road network capacity at critic locations. This thesis focuses on estimation of the type and level of parking utilization and violations in METU Campus, so that smart parking management strategies can be recommended for development of a more sustainable campus transportation policies. Smart parking management requires an understanding of land use, parking supply and demand, driver needs, behaviors, and perception of the commuters, in the scope of parking management. Thus , within the study, parking space inventory, parking survey were conducted and a smart campus transportation survey was utilized. After this comprehensive evaluation, a campus-wide parking management strategy plan that promote smart mobility within the campus was proposed within the campus, in 7 stages . In addition, a regional strategy plan, including the locations, and application of the proposed parking pricing strategy, and the areas where parking should be prohibited, has been created. Giderek artan araç sayısı ve teknolojik gelişmelerle birlikte, ulaşımla ilgili sosyal problemler; Akıllı Ulaşım Sistemleri’nin bir parçası olan sistematik ve akıllı çözümlerle ele alınmalıdır. Park yönetimi, sınırlı otopark kapasitelerinin daha fazla yol kullanıcısı tarafından verimli ve adil bir şekilde kullanılabildiği Akıllı Ulaşım Sistemleri uygulama alanıdır. Ancak; otopark arzının ve parklanma talebinin kapsamının, ayrıca kullanılacak olan herhangi politika ve teknolojik ürüne verilmesi beklenen karşılığın belirlenmesi gerekli ön şarttır. Yapılı çevre olan Orta Doğu Teknik Üniversitesi (ODTÜ) kampüsü parklanmaya olan talebin artmasına rağmen, içerisindeki park yeri kapasitesinin sınırlı olmasından dolayı, parklanma ile ilgili problemlerle yüzleşmektedir. Son zamanlarda park ihlalleri, kampüste araç sayısının fazlalığından dolayı artmaktadır. Olumsuz çevresel etkilerin yanı sıra park ihlalleri; kritik konumlarda trafik sıkışıklığı ve karayolu ağı kapasitesinin kaybı oluşturması nedeniyle. kampüs trafiğinin akışını ve güvenliğini azaltmaya başlamıştır. M.S. - Master of Science
Abstract
With the ever-increasing number of vehicles and technological advancements, transportation-related social problems are addressed with more systematic and smarter solutions, [...]
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System for improvement of the QoE in public transportation
B. Neto

Collection of open thesis in transport research (2020). Vol. 2020, 39

Abstract
Due to the increase of the greenhouse effect and consequent climate changes, over the years, plans for reducing carbon emissions have been presented and discussed. One of the best ways for reducing and neutralizing carbon emissions is to use of collective transports, which is also one of the most accessible forms of contribution for the general public. However, it is not always simple or appealing. Therefore, one of the main goals of this work was to contribute in reducing the carbon emissions and to increase the sustainability of the urban areas. With that purpose in mind, a system that provides real-time information to the user was implemented, in order to encourage more people to use public transportation — and its impact was measured. The selected information was the following: real-time location of the bus, estimated time of arrival of the bus, route mapping, information about each stop. This information is presented to the user through dynamic signaling at main stops and internet services for computers and mobile phones. The developed work, in order to achieve the objectives mentioned, was to create a complete system of real-time information for public transportation in the Centro Region of Portugal, including a mobile app, a website and the backend for all the service and communications. The impact was measured by conducting surveys, presenting the project to the common population on an early state and, posteriorly, demonstrating and encouraging the use of the functional prototype. Devido ao aumento do efeito de estufa e consequentes alterações climáticas, ao longo dos anos, têm-se vindo a apresentar e a debater planos para a redução das emissões de carbono. Um dos caminhos indicados para a redução e neutralização do carbono é o uso de transportes coletivos, sendo também uma das formas de contribuição mais acessível ao público geral. Porém, nem sempre é algo simples ou apelativo. Assim, um dos grandes objetivos deste trabalho foi contribuir para reduzir as emissões de carbono e aumentar a sustentabilidade nas áreas urbanas. Com este propósito em mente, foi implementado um sistema que fornece informação ao utilizador em tempo real, de forma a encorajar mais pessoas a utilizarem os transportes públicos — e o impacto final foi medido. A informação selecionada foi a seguinte: localização em tempo real do autocarro, tempo estimado de chegada do autocarro, mapa da rota, informação sobre cada paragem. Esta informação é apresentada ao utilizador através de sinalização dinâmica nas paragens principais e de serviços de internet para computador e telemóvel. O trabalho desenvolvido, de forma a atingir os objetivos mencionados, consistiu em criar um sistema em tempo real completo para transportes públicos na Região Centro de Portugal, incluindo uma aplicação móvel, um website e um servidor backend para estabelecer os serviços e comunicações. O impacto foi medido através de inquéritos, apresentando o projeto à população numa fase inicial e, posteriormente, demonstrando e incentivando o uso do protótipo funcional. Mestrado em Engenharia Informátic
Abstract
Due to the increase of the greenhouse effect and consequent climate changes, over the years, plans for reducing carbon emissions have been presented and discussed. One of [...]
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Enhancing Geospatial Preparedness for Disaster Management through the work of development organisations
R. Hernaiz

Collection of open thesis in transport research (2020). Vol. 2020, 36

Abstract
thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management Depending on the complexity of a disaster and the local capacities, international organizations and multidisciplinary response teams might be involved in the response. Geographic Information Systems (GIS) are used for coordination and information sharing. However, geospatial preparedness is necessary: reliable up to date geodata, tools, and people with the knowledge to use those tools. In least-developed countries the lack of geospatial preparedness, particularly geospatial pre-disaster information, hinders disaster response. In those places, the United Nations Office for the Coordination of Humanitarian Affairs creates a framework for cooperation with the Coordinated Data Scramble Initiative where Information Management Officers (IMOs) from different organisations are supported by volunteers and technical communities to provide ad-hoc datasets and infrastructure to use GIS. Nevertheless, long-term solutions are needed. Before the disaster, Non-Governmental Organizations (NGOs) might already be using GIS to implement development projects. Based on the theoretical concept of disaster management and development as a learning circle, this investigation proposes the engagement of development NGOS working in disaster-prone areas to enhance geospatial preparedness. The research was based on a multi-method approach including the study of the body of literature, authoritative reports, and repositories and databases, monitorization of the tools used during responses to real emergencies, and semi-structured interviews to IMOs. Finally, the study concluded with an online survey with a worldwide sample of more than 200 development NGOs. The result show that disaster response requires reliable and up to date geodata which is not always the case. Humanitarian missions often rely on OpenStreetMap as a source of information to overcome this limitation. Therefore, improving OpenStreetMap would improve geospatial preparedness. Many development NGOs use digital geographic information, mostly open-data. They could indeed improve geospatial preparedness allowing community empowerment while conveying relevant pre-disaster datasets to the humanitarian missions. This bottom-up approach would allow for the inclusion of information relevant to the community in the disaster response decision-making process. There is, however, a limitation; most of these development NGOs are not familiar with the platform used by the humanitarian community (i.e., OpenStreetMap). Therefore, the sustainability of this synergic approach requires further harmonization between development and humanitarian organizations working for the wellbeing of the same communitie
Abstract
thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management Depending on the complexity of a disaster and the local capacities, [...]
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Using Unreal Engine as an engineering tool for traffic simulation and analysis
J. Manjón Prado

Collection of open thesis in transport research (2020). Vol. 2020, 34

Abstract
This project studies the aggravating problem of road traffic and congestion, and some of its solutions: autonomous cars and traffic simulation software. Unreal Engine is presented as a new option for simulating a traffic environment. An application is programmed that allows the user to create and edit roadtracks by clicking and dragging in the editor, along with autonomous vehicle models to populate them with. The simulator is tested using different scenarios and obtaining relevant data. Finally, the obtained conclusions are mentioned, along with ideas and guidelines for future developmen
Abstract
This project studies the aggravating problem of road traffic and congestion, and some of its solutions: autonomous cars and traffic simulation software. Unreal Engine is presented [...]
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