Documents published in 2019 : Scipedia

Constructional solutions for increasing the capacities of cable cars
S. Težak, M. Lep

Collection of open conferences in research transport (2019). Vol. 2019, 163

Abstract
Cableways have some potential to be used in urban public transportation, particularly uni-directional aerial cable cars with circulating cabins, called gondolas. They have several advantages, but two major problems must be solved: the capacity and the operating speed are not competitive when compared to other means of urban mass transport because of boarding procedures and slowing down and accelerating on intermediate stations. This paper presents constructional solutions that address these problems. It proposes that boarding takes place on at least two platforms; these could be on the same level or on separate levels. At intermediate stations certain cabins are diverted to an extra platform while the majority of cabins travel with unreduced speed. Following this constructional approach, the nominal capacity of gondolas could be doubled while increasing the operational travel speed on lines with lot of intermediate stops.
Abstract
Cableways have some potential to be used in urban public transportation, particularly uni-directional aerial cable cars with circulating cabins, called gondolas. They have [...]
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A Digital Image Processing Pipeline for Modelling of Realistic Noise in Synthetic Images
O. Hellwich, A. Ley, O. Bielova, R. Hänsch

Collection of open conferences in research transport (2019). Vol. 2019, 162

Abstract
The evaluation of computer vision methods on synthetic images offers control over scene, object, and camera properties. The disadvantage is that synthetic data usually lack many of the effects of real cameras that pose the actual challenge to the methods under investigation. Among those, noise is one of the effects more difficult to simulate as it changes the signal at an early stage and is strongly influenced by the camera’s internal processing chain. The resulting noise is highly complex, intensity dependent, as well as spatially and spectrally correlated. We propose to transform synthetic images into the raw format of digital cameras, alter them with a physically motivated noise model, and then apply a processing chain that resembles a digital camera. Experiments show that the resulting noise exhibits a strong similarity to noise in real digital images, which further decreases the gap between synthesized images and real photographs.
Abstract
The evaluation of computer vision methods on synthetic images offers control over scene, object, and camera properties. The disadvantage is that synthetic data usually lack [...]
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Data-Driven Location Annotation for Fleet Mobility Modeling
G. R., N. M., S. F.

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

Abstract
The large availability of mobility data allows studying human behavior and human activities. However, this massive and raw amount of data generally lacks any detailed semantics or useful categorization. Annotations of the locations where the users stop may be helpful in a number of contexts, including user modeling and profiling, urban planning, activity recommendations, and can even lead to a deeper understanding of the mobility evolution of an urban area. In this paper, we foster the expressive power of individual mobility networks, a data model describing users' behavior, by defining a data-driven procedure for locations annotation. The procedure considers individual, collective, and contextual features for turning locations into annotated ones. The annotated locations own a high expressiveness that allows generalizing individual mobility networks, and that makes them comparable across different users. The results of our study on a dataset of trucks moving in Greece show that the annotated individual mobility networks can enable detailed analysis of urban areas and the planning of advanced mobility applications.
Abstract
The large availability of mobility data allows studying human behavior and human activities. However, this massive and raw amount of data generally lacks any detailed semantics [...]
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Chemical technology case study in cemented paste backfill – Newmont’s Tanami Gold Mine
A. Flemmer, Z. Martic, J. Gelson, R. Salter

Collection of open conferences in research transport (2019). Vol. 2019, 161

Abstract
Cemented paste fill operations have been in operation for many years in Australia. In recent years, rapid advances have been made in chemical technologies improving mining backfill operations. BASF’s in\u001Edepth analysis and laboratory work on both the physical and chemical parameters involved in backfill operations has been instrumental in re shaping this pathway. Many physical parameters can be improved via plant modifications; however, at significant expense to the mine. Even with peak plant performance, further optimisation can only be achieved in a cost-effective manner via improved chemistry. This is where chemical admixtures come into their own. The feed to the backfill plant uses dry excavated tailings. The Tanami plant was unable to operate to the specified solids contents due to variations in chemistry, fineness and high clay content of the tailings, which in turn affected the desired throughput and strength consistency of the fill. Higher cement contents were also required to reliably maintain the desired strengths. The chemical solution proposed by BASF increased solids content, reduced friction and pressures in the pipelines, and maintained a more consistent paste throughput with consistent strengths. This case study describes the processes employed by BASF for Newmont to identify and resolve issues encountered in the backfill operation at their Tanami Gold Mine. The case study discusses topics from initial sampling, analysis and lab testing to final onsite trials of the chemical admixture solution provided. The benefits to the mine are summarised in the paper.
Abstract
Cemented paste fill operations have been in operation for many years in Australia. In recent years, rapid advances have been made in chemical technologies improving mining [...]
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Steering hyper-giants' traffic at scale
J. Zerwas, I. Poese, E. Pujol, G. Smaragdakis, A. Feldmann

Collection of open conferences in research transport (2019). Vol. 2019, 160

Abstract
Large content providers, known as hyper-giants, are responsible for sending the majority of the content traffic to consumers. These hyper-giants operate highly distributed infrastructures to cope with the ever-increasing demand for online content. To achieve 40 commercial-grade performance of Web applications, enhanced end-user experience, improved reliability, and scaled network capacity, hyper-giants are increasingly interconnecting with eyeball networks at multiple locations. This poses new challenges for both (1) the eyeball networks having to perform complex inbound traffic engineering, and (2) hyper-giants having to map end-user requests to appropriate servers. We report on our multi-year experience in designing, building, rolling-out, and operating the first-ever large scale system, the Flow Director, which enables automated cooperation between one of the largest eyeball networks and a leading hyper-giant. We use empirical data collected at the eyeball network to evaluate its impact over two years of operation. We find very high compliance of the hyper-giant to the Flow Director’s recommendations, resulting in (1) close to optimal user-server mapping, and (2) 15% reduction of the hyper-giant’s traffic overhead on the ISP’s long-haul links, i.e., benefits for both parties and end-users alike. EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe
Abstract
Large content providers, known as hyper-giants, are responsible for sending the majority of the content traffic to consumers. These hyper-giants operate highly distributed [...]
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Correct-by-Construction Advanced Driver Assistance Systems Based on a Cognitive Architecture
M. Lahijanian, F. Eiras, M. Kwiatkowska

Collection of open conferences in research transport (2019). Vol. 2019, 159

Abstract
Research into safety in autonomous and semi-autonomous vehicles has, so far, largely been focused on testing and validation through simulation. Due to the fact that failure of these autonomous systems is potentially life-endangering, formal methods arise as a complementary approach. This paper studies the application of formal methods to the verification of a human driver model built using the cognitive architecture ACT-R, and to the design of correct-by-construction Advanced Driver Assistance Systems (ADAS). The novelty lies in the integration of ACT-R in the formal analysis and an abstraction technique that enables finite representation of a large dimensional, continuous system in the form of a Markov process. The situation considered is a multi-lane highway driving scenario and the interactions that arise. The efficacy of the method is illustrated in two case studies with various driving conditions. Comment: Proceedings at IEEE CAVS 2019
Abstract
Research into safety in autonomous and semi-autonomous vehicles has, so far, largely been focused on testing and validation through simulation. Due to the fact that failure [...]
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VANET distributed data fusion for traffic management
V. Cherfaoui, R. Guyard

Collection of open conferences in research transport (2019). Vol. 2019, 158

Abstract
International audience; In this article, we propose a distributed fusion algorithm to detect traffic congestion through the exchange of messages in vehicle network. This algorithm is based on the Dempster-Shafer theory that manages the uncertainties on data and sources of information. Each vehicle updates its database with local measurements (speed and interdistance) and information received from other vehicles and can calculate its route. Thanks to the collaboration, smart cars can avoid congested roads and take a better path to their destination. Several variants of the algorithm are studied and compared to a centralized approach through experiments carried out on the SUMO simulator using real urban road networks.
Abstract
International audience; In this article, we propose a distributed fusion algorithm to detect traffic congestion through the exchange of messages in vehicle network. This algorithm [...]
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Workflow Design Analysis for High Resolution Satellite Image Analysis
M. Turilli, I. Paraskevakos, B. Gonçalves, H. Lynch, S. Jha

Collection of open conferences in research transport (2019). Vol. 2019, 157

Abstract
Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery provide an effective dataset for large scale surveys. Convolutional Neural Networks have successfully been employed to analyze such imagery and detect large animals. As the datasets increase in volume, O(TB), and number of images, O(1k), utilizing High Performance Computing (HPC) resources becomes necessary. In this paper, we investigate a task-parallel data-driven workflows design to support imagery analysis pipelines with heterogeneous tasks on HPC. We analyze the capabilities of each design when processing a dataset of 3,000 VHR satellite images for a total of 4~TB. We experimentally model the execution time of the tasks of the image processing pipeline. We perform experiments to characterize the resource utilization, total time to completion, and overheads of each design. Based on the model, overhead and utilization analysis, we show which design approach to is best suited in scientific pipelines with similar characteristics. Comment: 10 page
Abstract
Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery provide an effective [...]
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The pipeline transport of high density slurries — a historical review of past mistakes, lessons learned and current technologies
A. Paterson

Collection of open conferences in research transport (2019). Vol. 2019, 156

Abstract
There is a great deal of misinformation in the industry on pumping high density, viscous slurries. These misconceptions become “accepted truths” as time goes on and at best hinder, and at worst stop, the implementation of appropriate technology. Unfortunately the root of these misconceptions is often due to experiences gained on poorly understood, designed or implemented systems. Advances in a technology can only be realised by accepting that the mistakes of the past can be rectified and learned from. Unfortunately this does not readily happen in an industry that is resistant to change. The objective of this paper is to address these issues by tracing the historical development of high density pumping and why the problems of the past are not necessarily the same problems of today. It is accepted that many of the fundamental problems cannot be resolved, and continued improvements in ore processing will mean that new challenges will arise. However, there is a better understanding of how to deal with the issues practically by using the latest developments in pump and pipeline technology.
Abstract
There is a great deal of misinformation in the industry on pumping high density, viscous slurries. These misconceptions become “accepted truths” as time goes on and at [...]
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Development of Information Support System (ISS) Application for Organization Performance Improvement: Case in Tyre Manufacturer and Air Transport Company
A. Pratama, S. Awibowo, F. Thomafi, N. Puteri

Collection of open conferences in research transport (2019). Vol. 2019, 155
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Neural Point Cloud Rendering via Multi-Plane Projection
Z. Li, B. Zeng, P. Dai, Y. Zhang, S. Liu

Collection of open conferences in research transport (2019). Vol. 2019, 154

Abstract
We present a new deep point cloud rendering pipeline through multi-plane projections. The input to the network is the raw point cloud of a scene and the output are image or image sequences from a novel view or along a novel camera trajectory. Unlike previous approaches that directly project features from 3D points onto 2D image domain, we propose to project these features into a layered volume of camera frustum. In this way, the visibility of 3D points can be automatically learnt by the network, such that ghosting effects due to false visibility check as well as occlusions caused by noise interferences are both avoided successfully. Next, the 3D feature volume is fed into a 3D CNN to produce multiple layers of images w.r.t. the space division in the depth directions. The layered images are then blended based on learned weights to produce the final rendering results. Experiments show that our network produces more stable renderings compared to previous methods, especially near the object boundaries. Moreover, our pipeline is robust to noisy and relatively sparse point cloud for a variety of challenging scenes. Comment: 17 page
Abstract
We present a new deep point cloud rendering pipeline through multi-plane projections. The input to the network is the raw point cloud of a scene and the output are image or [...]
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Research on Urban Logistics Distribution Based on Dynamic Demand
G. Huang, X. Zhang

Collection of open conferences in research transport (2019). Vol. 2019, 153
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Modelling and Analysis of Flow Rate and Pressure Head in Pipelines
R. Jafari, C. Vargas-Jarillo, S. Razvarz

Collection of open conferences in research transport (2019). Vol. 2019, 152

Abstract
Currently, various approaches with several utilities are proposed to identify damage in the pipeline. The pipeline system is modeled in the form of a distributed parameter system, such that the state space related to the distributed parameter system contains infinite dimension. In this paper, a novel technique is proposed to analyze and model the flow in the pipeline. Important theorems are proposed for testing the observability as well as controllability of the proposed model.
Abstract
Currently, various approaches with several utilities are proposed to identify damage in the pipeline. The pipeline system is modeled in the form of a distributed parameter [...]
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Reconfigurable Stationary Battery with Adaptive Cell Switching for Electric Vehicle Fast-Charging
T. Gabderakhmanova, J. Engelhardt, M. Marinelli, G. Rohde

Collection of open conferences in research transport (2020). Vol. 2020, 48

Abstract
In this study, we introduce a battery energy storage system (BESS) with reconfigurable cell topology as the direct power source for fast-charging of electric vehicles (EVs). In the proposed scenario, the BESS is following the charging request of the EV by changing its cell topology in a real time fashion. The BESS is modelled at the cell level in order to demonstrate the reconfigurable design, and linked with an EV model. The simulation results confirm that the BESS can maintain a balanced level of its cell states while following the voltage request of the EV with satisfactory precision. However, the approach of adaptive cell switching shows to be not sufficient for fulfilling the current request. Therefore, complementary solutions are necessary to achieve a suitable control of the charging current.
Abstract
In this study, we introduce a battery energy storage system (BESS) with reconfigurable cell topology as the direct power source for fast-charging of electric vehicles (EVs). [...]
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Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data
D. Rukhovich, M. Rufli, D. Mouritzen, R. Kaestner, A. Velizhev

Collection of open conferences in research transport (2019). Vol. 2019, 151

Abstract
This paper addresses the problem of scale estimation in monocular SLAM by estimating absolute distances between camera centers of consecutive image frames. These estimates would improve the overall performance of classical (not deep) SLAM systems and allow metric feature locations to be recovered from a single monocular camera. We propose several network architectures that lead to an improvement of scale estimation accuracy over the state of the art. In addition, we exploit a possibility to train the neural network only with synthetic data derived from a computer graphics simulator. Our key insight is that, using only synthetic training inputs, we can achieve similar scale estimation accuracy as that obtained from real data. This fact indicates that fully annotated simulated data is a viable alternative to existing deep-learning-based SLAM systems trained on real (unlabeled) data. Our experiments with unsupervised domain adaptation also show that the difference in visual appearance between simulated and real data does not affect scale estimation results. Our method operates with low-resolution images (0.03 MP), which makes it practical for real-time SLAM applications with a monocular camera.
Abstract
This paper addresses the problem of scale estimation in monocular SLAM by estimating absolute distances between camera centers of consecutive image frames. These estimates [...]
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Modern Military ATM Systems and their Optimalization in Integrated Civil and Military ATC
B. Marik, I. Marik, I. Marik

Collection of open conferences in research transport (2019). Vol. 2019, 150

Abstract
Military ATM systems represents important part of air traffic control systems in the national and international airspace of Europe. In the light of the need for the increasingly efficient use of limited airspace, it is gradually transformed into the conditions of integrated civil-military air traffic management, both nationally and internationally, in which the civilian commercial sector creates unprecedented pressure to prioritize civilian airspace use and civilian air traffic management. Military A TM systems that have been developed so far as parallel versions of civilian ATM systems, partially adapted to the specific efforts of military air forces, have led to a gradual reduction of their scope and efficiency gains while reducing costs. The methods and practical possibilities of this seemingly contradictory approach are described in this text, many of these methods were implemented in practice in the national conditions of the Czech Republic and at international level of air traffic control and can therefore be considered appropriate to meet the requirements imposed on them.
Abstract
Military ATM systems represents important part of air traffic control systems in the national and international airspace of Europe. In the light of the need for the increasingly [...]
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Environmental Management in Republic of Crimea Represented by Modeling Use of Big-Diameter Pipelines in Various Operation Modes
M. Bandurin, A. Mykhailin, V. Nefedov

Collection of open conferences in research transport (2019). Vol. 2019, 149
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Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks
B. Uzkent, V. Sarukkai, A. Jain, S. Ermon

Collection of open conferences in research transport (2019). Vol. 2019, 148

Abstract
Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit coverage, making ground information extraction more difficult. Existing pipelines typically perform cloud removal with simple temporal composites and hand-crafted filters. In contrast, we cast the problem of cloud removal as a conditional image synthesis challenge, and we propose a trainable spatiotemporal generator network (STGAN) to remove clouds. We train our model on a new large-scale spatiotemporal dataset that we construct, containing 97640 image pairs covering all continents. We demonstrate experimentally that the proposed STGAN model outperforms standard models and can generate realistic cloud-free images with high PSNR and SSIM values across a variety of atmospheric conditions, leading to improved performance in downstream tasks such as land cover classification. Comment: Accepted to WACV 2020
Abstract
Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit coverage, making [...]
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Characterizing player types in gamified geodata acquisition - An exploratory analysis of StreetComplete
H. Lorei, R. Westerholt, A. Zipf

Collection of open conferences in research transport (2019). Vol. 2019, 146

Abstract
Lorei et al. (2019). Characterizing player types in gamified geodata acquisition - An exploratory analysis of StreetComplete In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 33-34. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3387723
Abstract
Lorei et al. (2019). Characterizing player types in gamified geodata acquisition - An exploratory analysis of StreetComplete In: Minghini, M., Grinberger, A.Y., Juhász, [...]
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The Effect Of Traffic Congestion On Quality Of Community Life
W. Ghazali

Collection of open conferences in research transport (2019). Vol. 2019, 145
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Modeling and analysis of alternative distribution and Physical Internet schemes in urban area
H. Jiang, E. Ballot, S. Pan

Collection of open conferences in research transport (2019). Vol. 2019, 144

Abstract
International audience; Urban logistics is becoming more complicated and costlier due to new challenges in recent years. Since the main problem lies on congestion, the clean vehicle is not necessarily the most effective solution. There is thus a need to redesign the logistics networks in the city. This paper proposes a methodology to evaluate different distribution schemes in the city among which we find the most efficient and sustainable one. External impacts are added to the analysis of schemes, including accident, air pollution, climate change, noise, and congestion. An optimization model based on an analytical model is developed to optimize transportation means and distribution schemes. Results based on Bordeaux city show that PI scheme improves the performances of distribution.
Abstract
International audience; Urban logistics is becoming more complicated and costlier due to new challenges in recent years. Since the main problem lies on congestion, the clean [...]
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Testing steelfibroconcrete centrifuged specimens of pipes used in drainage and water disposal systems at places of automobile and railway transport heavy traffic
M. Kuznetsov, A. Kuznetsov, A. Kuznetsov, V. Dubinina, A. Noskov

Collection of open conferences in research transport (2019). Vol. 2019, 142

Abstract
Ferroconcrete pipes, used in drainage and water disposal systems of roads, works in conditions, in which the direction of the main tensile stresses is either unknown, or can change during exploitation. One of the ways of solving this problem is using of steel fibrous concrete, i.e. concrete on hydraulic tenacious substances with addition of reinforcing elements in the form of short lengths (fibers). Using of steel fibrous concrete allows to get the construction of low pressure centrifuged pipe for drainage and water disposal systems at places of automobile and railway transport heavy traffic with higher tensile and bending strength, crack resistance for the work under conditions when the direction of the main tensile stresses is unknown. © 2019 Published under licence by IOP Publishing Ltd.
Abstract
Ferroconcrete pipes, used in drainage and water disposal systems of roads, works in conditions, in which the direction of the main tensile stresses is either unknown, or can [...]
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Fusion of Sensors Data in Automotive Radar Systems: A Spectral Estimation Approach
M. Zorzi, J. Karlsson, B. Zhu, A. Ferrante

Collection of open conferences in research transport (2019). Vol. 2019, 141

Abstract
To accurately estimate locations and velocities of surrounding targets (cars) is crucial for advanced driver assistance systems based on radar sensors. In this paper we derive methods for fusing data from multiple radar sensors in order to improve the accuracy and robustness of such estimates. First we pose the target estimation problem as a multivariate multidimensional spectral estimation problem. The problem is multivariate since each radar sensor gives rise to a measurement channel. Then we investigate how the use of the cross-spectra affects target estimates. We see that the use of the magnitude of the cross-spectrum significantly improves the accuracy of the target estimates, whereas an attempt to compensate the phase lag of the cross-spectrum only gives marginal improvement. This paper may be viewed as a first step towards applying high-resolution methods that builds on multidimensional multivariate spectral estimation for sensor fusion. Comment: 6 pages in IEEE conference template; accepted for presentation in CDC 2019
Abstract
To accurately estimate locations and velocities of surrounding targets (cars) is crucial for advanced driver assistance systems based on radar sensors. In this paper we derive [...]
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Attentional orienting in real and virtual 360-degree environments
R. Soret, V. Peysakhovich, C. Hurter

Collection of open conferences in research transport (2019). Vol. 2019, 140

Abstract
International audience; We investigate the mechanisms of attentional orienting in a 360-degree virtual environments. Through the use of Posner's paradigm, we study the effects of different attentional guidance techniques designed to improve information processing. The most efficient technique will be applied to a procedure learning tool in virtual reality and a remote air traffic control tower. The eye-tracker allows us to explore the differential effects of overt and covert orienting, to estimate the effectiveness of visual research and to use it as a technique for interaction in virtual reality.
Abstract
International audience; We investigate the mechanisms of attentional orienting in a 360-degree virtual environments. Through the use of Posner's paradigm, we study the effects [...]
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SIMNORAT - Final Conference - Case Study Posters
Collection of open conferences in research transport (2021). Vol. 2019, 139
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Forecasting pedestrian trajectory with machine-annotated training data
A. Ross, V. Sanchez, O. Styles

Collection of open conferences in research transport (2019). Vol. 2019, 138

Abstract
Reliable anticipation of pedestrian trajectory is imperative for the operation of autonomous vehicles and can significantly enhance the functionality of advanced driver assistance systems. While significant progress has been made in the field of pedestrian detection, forecasting pedestrian trajectories remains a challenging problem due to the unpredictable nature of pedestrians and the huge space of potentially useful features. In this work, we present a deep learning approach for pedestrian trajectory forecasting using a single vehicle-mounted camera. Deep learning models that have revolutionized other areas in computer vision have seen limited application to trajectory forecasting, in part due to the lack of richly annotated training data. We address the lack of training data by introducing a scalable machine annotation scheme that enables our model to be trained using a large dataset without human annotation. In addition, we propose Dynamic Trajectory Predictor (DTP), a model for forecasting pedestrian trajectory up to one second into the future. DTP is trained using both human and machine-annotated data, and anticipates dynamic motion that is not captured by linear models. Experimental evaluation confirms the benefits of the proposed model. Comment: 6 pages, 5 figures. To appear in the proceedings of the 2019 IEEE Intelligent Vehicles Symposium (IV)
Abstract
Reliable anticipation of pedestrian trajectory is imperative for the operation of autonomous vehicles and can significantly enhance the functionality of advanced driver assistance [...]
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Urban Underground Infrastructure Monitoring IoT: The Path Loss Analysis
A. Salam, S. Shah

Collection of open conferences in research transport (2019). Vol. 2019, 137

Abstract
The extra quantities of wastewater entering the pipes can cause backups that result in sanitary sewer overflows. Urban underground infrastructure monitoring is important for controlling the flow of extraneous water into the pipelines. By combining the wireless underground communications and sensor solutions, the urban underground IoT applications such as real time wastewater and storm water overflow monitoring can be developed. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. It has been shown that the communication range of up to 4 kilometers can be achieved from an underground transmitter when communicating through 10cm thick asphalt layer.
Abstract
The extra quantities of wastewater entering the pipes can cause backups that result in sanitary sewer overflows. Urban underground infrastructure monitoring is important for [...]
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Port-Hamiltonian Models for Flow of Incompressible Fluids in Rigid Pipelines with Faults
G. Besancon, L. Torres

Collection of open conferences in research transport (2019). Vol. 2019, 136

Abstract
This paper presents port-Hamiltonian models for describing flow dynamics of incompressible fluids in rigid pipelines with faults. Two types of faults are addressed in this paper: leaks and partial blockages. In order to facilitate the understanding of the modeling, the proposed formulation is introduced starting from the analogy between electrical and hydraulic circuits. Thanks to the port-Hamiltonian formalism the models proposed here have a particular structure that makes them plug-in and modular, so that they can be interconnected for building holistic models for faulty water distribution networks.
Abstract
This paper presents port-Hamiltonian models for describing flow dynamics of incompressible fluids in rigid pipelines with faults. Two types of faults are addressed in this [...]
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Evaluation of strength, fatigue, durability and damage to the material in the machine elements using physical parameters and criteria
N. Shtyrov

Collection of open conferences in research transport (2019). Vol. 2019, 135

Abstract
This paper presents the main physical parameters, dependencies, calculation methods in the physical structural-energy theory of the strength of a deformed solid. The initial physical and mechanical parameters of the strength of steel 45 were determined analytically. The physical methods were used to calculate the durability, fatigue, and steel damage for non-stationary mechanical and thermal loads. The relationship between physical and mechanical strength parameters is analytically determined. The results of calculations of the modified characteristics of the strength of the damaged material are presented, plastic deformations, cyclic stresses of arbitrary shape, and temperature conditions are taken into account. The originality of the study consists in that we used our own program for calculating the new characteristics of the damaged material for different stress functions. The application value of the research is that the physical method allows to analyze the data of load sensors, indentation according to ISO 14577 in the elements of machines. The physical parameters of the material and the new theoretical calculation methods can be used to control the state of the strength of the machinery mechanisms during operation.
Abstract
This paper presents the main physical parameters, dependencies, calculation methods in the physical structural-energy theory of the strength of a deformed solid. The initial [...]
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Estimating Socioeconomic Status via Temporal-Spatial Mobility Analysis -- A Case Study of Smart Card Data
X. Fu, H. Huang, S. Ding, T. Zhao

Collection of open conferences in research transport (2019). Vol. 2019, 134

Abstract
The notion of socioeconomic status (SES) of a person or family reflects the corresponding entity's social and economic rank in society. Such information may help applications like bank loaning decisions and provide measurable inputs for related studies like social stratification, social welfare and business planning. Traditionally, estimating SES for a large population is performed by national statistical institutes through a large number of household interviews, which is highly expensive and time-consuming. Recently researchers try to estimate SES from data sources like mobile phone call records and online social network platforms, which is much cheaper and faster. Instead of relying on these data about users' cyberspace behaviors, various alternative data sources on real-world users' behavior such as mobility may offer new insights for SES estimation. In this paper, we leverage Smart Card Data (SCD) for public transport systems which records the temporal and spatial mobility behavior of a large population of users. More specifically, we develop S2S, a deep learning based approach for estimating people's SES based on their SCD. Essentially, S2S models two types of SES-related features, namely the temporal-sequential feature and general statistical feature, and leverages deep learning for SES estimation. We evaluate our approach in an actual dataset, Shanghai SCD, which involves millions of users. The proposed model clearly outperforms several state-of-art methods in terms of various evaluation metrics. Comment: 9 pages, double column, IEEE ICCCN 2019
Abstract
The notion of socioeconomic status (SES) of a person or family reflects the corresponding entity's social and economic rank in society. Such information may help applications [...]
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Prospects for the use of alternative fuels and energy by road transport in Russia
E. Magaril, A. Golubeva

Collection of open conferences in research transport (2019). Vol. 2019, 133

Abstract
Road transport is one of the main consumers of petroleum products and sources of air pollution. In the conditions of Russia's fast-growing vehicle fleet, it is necessary to develop and implement effective measures to reduce the consumption of scarce oil fuels and stimulate the use of alternative eco-friendly fuels. The aim of this work is to assess the prospects for the use of alternative fuels and energy by cars in Russia. This paper outlines the main ways of reducing the gasoline and diesel fuel consumption by road transport, including the use of the motor fuel alternative types. As the most promising direction of alternative energy development in the road transport sector regarding Russia's conditions, a transition to gas-cylinder fuel is proposed. This study presents the main problems of road transport gasification and the ways to solve them. The effective actions in the selected fields will reduce the consumption of scarce fuel and energy resources and enable improvement of the environmental situation in megalopolises. © 2019 WIT Pre
Abstract
Road transport is one of the main consumers of petroleum products and sources of air pollution. In the conditions of Russia's fast-growing vehicle fleet, it is necessary to [...]
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Internet of Things Services Based Traffic Congestion Monitoring for Smart Riyadh City: A Framework
A. Prabuwono

Collection of open conferences in research transport (2019). Vol. 2019, 131

Abstract
Internet of Things (IoT) technology connects physical things through the internet by creating a virtual identity for everything. It is based on the Internet, wireless sensor networks and detection technologies to realize intelligent recognition of the tagged traffic object and automatic tracking. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles that is resulting in grumbling by residents because of the massive delays, monetary losses and increased fuel wastage. There are currently few reliable services offered to residents from the traffic department enabling them to access traffic information. This research is to propose a traffic congestion framework for Riyadh road infrastructure and to apply IoT technology for monitoring traffic congestion. Sensing devices are used to identify the congestion of the traffic flow by providing multiple proposed services such as a vehicle counting, live streaming video and rerouting services. Users are able to access the services by using proposed mobile application connected to the internet, as those services are integrated with public map. Users are also able to identify the exact location where congestion occurs and an alternate solution can be provided easily. Business Process Execution Language (BPEL) is embedded as a supporting framework layer. Executable workflows are designed to combine the proposed services with the legacy Riyadh services as individual model. It clearly defines how the services are executed through the proposed models. In order to support the usability of this framework, a quantitative evaluation is provided.
Abstract
Internet of Things (IoT) technology connects physical things through the internet by creating a virtual identity for everything. It is based on the Internet, wireless sensor [...]
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Influence of Ambient Pressure on Performance of a Deep-sea Hydraulic Manipulator
Q. Zhang, C. Wang, L. Huo, S. Li, L. Du, Y. Chen, Q. Tian, Y. Bai

Collection of open conferences in research transport (2019). Vol. 2019, 130

Abstract
Deep-sea hydraulic manipulator is the most commonly used operation equipment for executing subsea operations in different applications. The increasing demands on underwater operational ease require the implementation of manipulator system which can maintain similar dynamic performance in different working conditions Considering the variations of seawater properties at different ocean depths, especially high hydrostatic pressure in deep-sea environment will make the kinematic viscosity of oil obviously increased, which has a significant influence on the performance of deep-sea hydraulic manipulator. The viscosity-pressure characteristics of working medium is tested. A detailed nonlinear mathematical model and related simulations considering the significant slender pipelines between valves and actuators due to the increased oil viscosity are conducted to analyze the ambient pressures against varying depths affecting the manipulator performance. The 115MPa online pressure experimental results indicate the joint response characteristics at different ambient pressures, which provides basis for response consistency control of deep-sea hydraulic manipulator.
Abstract
Deep-sea hydraulic manipulator is the most commonly used operation equipment for executing subsea operations in different applications. The increasing demands on underwater [...]
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CHARACTERISATION OF THE BARRIERS AND LIMITATIONS ON UTILISATION OF BIG DATA IN TRANSPORT: THE LEMO PROJECT
M. Hong, T. Teoh

Collection of open conferences in research transport (2019). Vol. 2019, 129

Abstract
The transport sector has continuously collected and analysed massive amounts of data, such as data from timetables, traffic news and air schedules. However, recent developments in the quantity, complexity and availability of such big data collected from and about transport systems, together with advances in information and communication technology, are presenting new opportunities to create more efficient and smarter transport and traffic systems for people and freight (Akerkar 2013). Also, ‘opening up’ data in transport by making it more widely available, and linking it with data from other sectors, is the part of the European strategy to improve transparency and encourage economic growth (Akerkar 2018).
Abstract
The transport sector has continuously collected and analysed massive amounts of data, such as data from timetables, traffic news and air schedules. However, recent developments [...]
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Designing the Siilinjärvi thickened tailings storage facility
E. Ruhanen, B. Henriksson, T. Fitton

Collection of open conferences in research transport (2019). Vol. 2019, 127

Abstract
This case study presents some of the key aspects of the design of the thickened tailings storage facility that recently commenced operation at Yara’s Siilinjarvi apatite mine in Finland. The mine is located near the Arctic Circle, and therefore operates in a cold climate. The tailings are also quite coarse (with a D90 of 700 microns), which creates challenges in the operation of a thickened tailings storage facility. This paper describes a series of pilot plant trials from 2007 to 2010 and demonstration plant beaching trials that took place in 2013 and 2014, not only in terms of the collection of data, but also with respect to the many engineering challenges that were overcome in the thickening and transport of the tailings slurry under these difficult conditions. The beaching trials provided good validating data for the design of the tailings storage facility. The beaching results are presented, along with some discussion of their comparison with the predicted beach slopes used in the tailings storage facility design. The paper further discusses and presents images of the thickeners, pumps, pipelines and tailings storage area.
Abstract
This case study presents some of the key aspects of the design of the thickened tailings storage facility that recently commenced operation at Yara’s Siilinjarvi apatite [...]
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Development and application of composites based on polytrifluorochlorethylene
O. Burya, S. Kalinichenko, A. Tomina, R. Rogatinsky

Collection of open conferences in research transport (2019). Vol. 2019, 126

Abstract
This paper provides results of an analytical study on the influence of the content of organic fiber Tanlon of the brand T700 on the physico-mechanical and tribological properties of organoplastics based on polytrifluorochlorethylene. As a result of the analysis it was found that introduction of 5-20 wt. % fiber Tanlon T700 leads to a positive effect: it increases modulus of elasticity, hardness and yield stress to 45-69, 30-60% and in 1,1-1,2 times respectively. It has been shown that, in conditions of friction without greasing implementation of filler, this solution positively affects on polymer: it reduces the coefficient of friction to 15-40% and wearing by two orders of magnitude (from 91.75 to 0.15). The practical value of these findings is that the developed composition can be used for production of mobile joints elements of machines and mechanisms that are used in various spheres of industry.
Abstract
This paper provides results of an analytical study on the influence of the content of organic fiber Tanlon of the brand T700 on the physico-mechanical and tribological properties [...]
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Energy-Optimal Coordination of Connected and Automated Vehicles at Multiple Intersections
L. Zhao, A. Malikopoulos, A. Mahbub, D. Assanis

Collection of open conferences in research transport (2019). Vol. 2019, 125

Abstract
Urban intersections, merging roadways, roundabouts, and speed reduction zones along with the driver responses to various disturbances are the primary sources of bottlenecks in corridors that contribute to traffic congestion. The implementation of connected and automated technologies can enable a novel computational framework for real-time control aimed at optimizing energy consumption and travel time. In this paper, we propose a decentralized energy-efficient optimal control framework for two adjacent intersections. We derive a closed-form analytical solution that includes interior boundary conditions and evaluate the effectiveness of the solution through simulation. Fuel consumption and travel time are significantly reduced compared to the baseline scenario designed with conventional fixed time signalized intersections.
Abstract
Urban intersections, merging roadways, roundabouts, and speed reduction zones along with the driver responses to various disturbances are the primary sources of bottlenecks [...]
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Estimating Public Charging Demand of Electric Vehicles
C. Seidel, J. Anderson, M. Hardinghaus

Collection of open conferences in research transport (2019). Vol. 2019, 124

Abstract
Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure. Document type: Article
Abstract
Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step [...]
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Poster Abstract: A flexible infinite HMM model for accurate characterization and segmentation of RTT timeseries
T. Chonavel, S. Vaton, M. Mouchet

Collection of open conferences in research transport (2019). Vol. 2019, 123

Abstract
International audience; The study of round-trip time (RTT) measurements on the Internet is of particular importance for improving real-time applications, enforcing QoS with traffic engineering, or detecting unexpected network conditions. On large timescales, from 1 hour to several days, RTT measurements exhibit characteristic patterns due to inter and intra-AS routing changes and traffic engineering, in addition to link congestion. We propose the use of a nonparametric Bayesian method to fully estimate HMM parameters from delay observations, including the number of states. We validate the model through three applications: the clustering of RIPE Atlas measurements, the detection of significant delay changes, and the reduction of the monitoring cost in routing overlays using Markov decision processes.
Abstract
International audience; The study of round-trip time (RTT) measurements on the Internet is of particular importance for improving real-time applications, enforcing QoS with [...]
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Detection- Tracking for Efficient Person Analysis: The DetTA Pipeline
U. Rafi, L. Beyer, S. Breuers, B. Leibel

Collection of open conferences in research transport (2019). Vol. 2019, 122

Abstract
In the past decade many robots were deployed in the wild, and people detection and tracking is an important component of such deployments. On top of that, one often needs to run modules which analyze persons and extract higher level attributes such as age and gender, or dynamic information like gaze and pose. The latter ones are especially necessary for building a reactive, social robot-person interaction. In this paper, we combine those components in a fully modular detection-tracking-analysis pipeline, called DetTA. We investigate the benefits of such an integration on the example of head and skeleton pose, by using the consistent track ID for a temporal filtering of the analysis modules' observations, showing a slight improvement in a challenging real-world scenario. We also study the potential of a so-called “free-flight” mode, where the analysis of a person attribute only relies on the filter's predictions for certain frames. Here, our study shows that this boosts the runtime dramatically, while the prediction quality remains stable. This insight is especially important for reducing power consumption and sharing precious (GPU-)memory when running many analysis components on a mobile platform, especially so in the era of expensive deep learning methods.
Abstract
In the past decade many robots were deployed in the wild, and people detection and tracking is an important component of such deployments. On top of that, one often needs [...]
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In-Vehicle IoT Platform Enabling the Virtual Sensor Concept: A Pothole Detection Use-case for Cooperative Safety
D. Brevi, C. Pastrone, E. Ferrera, I. Bosi

Collection of open conferences in research transport (2019). Vol. 2019, 121

Abstract
Nowadays the number of on-board sensors increases continuously due to their benefits in many different areas, such us driving efficiency, maintenance, autonomous driving, etc. Usually the vehicle itself and its users are those which take direct advantage from these benefits. By leveraging Internet-of-Things (IoT) technologies, it is possible to abstract data and functionalities provided by on-board sensors and actuators exposing relevant services outside the vehicle to external cloud-based applications and other vehicles. With these technologies the vehicle is thus transformed in an IoT object which can be part of external IoT platforms. This work focuses on the design and implementation of an in-vehicle IoT platform which exposes internal functionalities as IoT services enabling also the concept of “Virtual Sensor”, which leverages sensor fusion techniques to provide enhanced services combining raw data coming from on-board devices. This IoT platform solution is validated through a use case in which virtual real-time pothole detection sensor is implemented to evaluate the road surface conditions. In such use-case, multi-source sensing information - coming from 6LoWPAN sensors as well as Smartphones and Inertial Measurement Units - is fused, enabling IoT applications such as cooperative safety and early road maintenance.
Abstract
Nowadays the number of on-board sensors increases continuously due to their benefits in many different areas, such us driving efficiency, maintenance, autonomous driving, [...]
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Placement Optimization in Wireless Charging Systems under the Vector Model
E. Kerimakis, S. Nikoletseas, I. Katsidimas

Collection of open conferences in research transport (2019). Vol. 2019, 120

Abstract
—This paper addresses the optimization of power provisioning in systems of wireless energy transfer. In this context, a vectorial representation of wireless waves recently becomes a precious tool; being more reliable and precise thanone-dimensional models, it enables an increased potential for power maximization and control that before seemed impossible. We study the deployment of nodes and chargers for power maximization, for the first time under the vector model. In particular, we present both offline and approximation protocols and provide an evaluation of their performance. The main idea of our approach is to take advantage of the high precision offered by the vector model of WPT waves, in order to fine-tune the exact positioning of wireless chargers. The results of the conducted simulations demonstrate the advantages of our approaches in terms of power maximization; interestingly our findings suggest that even some slight optimization in the exact placement of chargers can significantly improved received power. Index Terms—Wireless Power Transfer, Vector Model, Ad-hoc Wireless Networks, Charger Placemen
Abstract
—This paper addresses the optimization of power provisioning in systems of wireless energy transfer. In this context, a vectorial representation of wireless waves recently [...]
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How to share what we used to own
S. Johnson, L. Harmer, D. Quinlan, A. Mausbach

Collection of open conferences in research transport (2019). Vol. 2019, 117

Abstract
This paper looks at the challenges to shift the mobility culture from ownership to sharing, in the context of ecological and autonomous vehicles. It proposes the observation of social aspects of car use and to build knowledge to educate people to live in a shared mobility scenario, and points out the importance of developing meaningful mobility experiences The paper looks into the context of rural transport and questions the monetization of shared mobility through the analysis of the Joyful Journeys project which observes the case of an elderly driver who gives lifts in a countryside village. It addition, it investigates through a new analysis of the RCA ´ s Frisbee car sharing project, aspects of placemaking and identity related to sharing cars. It concludes by indicating how the concepts of resilience, inclusive design and identity can develop in a shared mobility context. The paper proposes the development of sharing cars beyond business models, product and services development, but through designing a cultural change.
Abstract
This paper looks at the challenges to shift the mobility culture from ownership to sharing, in the context of ecological and autonomous vehicles. It proposes the observation [...]
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Public transportation prediction with convolutional neural networks
D. Panovski, T. Zaharia

Collection of open conferences in research transport (2019). Vol. 2019, 115

Abstract
International audience; Good, efficient and reliable public transportation systems are of crucial importance for all major cities today. In this paper, we propose a concrete solution to a particular problem: improve the prediction of the bus arrival time at each bus stop station on a given itinerary, by taking to account global and local traffic contexts. The main principle consists of modeling the traffic data as an image structure, adapted for applying CNN deep neural networks. The results obtained shows that the proposed approach outperforms traditional machine learning techniques, such as OLS (Ordinary Least Squares) or SVR (Support Vector Regression) with different kernels (RBF or Polynomial), with more than 18% better accuracy prediction, while being computationally faster.
Abstract
International audience; Good, efficient and reliable public transportation systems are of crucial importance for all major cities today. In this paper, we propose a concrete [...]
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Can DERs fully participate in emerging local flexibility tenders?
M. Petit, Y. Perez, F. Venegas

Collection of open conferences in research transport (2019). Vol. 2019, 114

Abstract
International audience; Distribution system operators' roles are evolving from a "fit-and-forget" approach towards an active management of their distribution grid. With this approach flexibility management at the local level can defer or avoid costly reinforcements and have a more efficient use of existing assets. Flexibility tenders are emerging as a mechanism that allow DSOs to procure flexibility for the medium to long term. This works proposed a modular framework to analyze the market rules of local flexibility tenders for the participation of distributed energy resources (DER), with a particular focus on demand response and electric vehicles, and applied it to the case study of UKPN's flexibility 2018/2019 tender and Enedis proposal for flexibility procurement. These tenders have been built to allow the participation of DER, but still there are barriers that may hinder their optimal participation, especially regarding connection procedures and baseline definition.
Abstract
International audience; Distribution system operators' roles are evolving from a "fit-and-forget" approach towards an active management of their distribution grid. With this [...]
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Higher than a kite: ADS-B communication analysis using a high-altitude balloon
F. Minucci, R. Calvo-Palomino, G. Bovet, B. Reynders, M. Schäfer, V. Lenders

Collection of open conferences in research transport (2019). Vol. 2019, 113

Abstract
Receiving signals on the 1090 MHz frequency, one of the most important radio frequencies used in aviation, is typically done using ground-based receivers. However, an increasing number of airborne or even space-based receivers also aim to receive these signals for applications such as air traffic surveillance and collision avoidance. In this paper, we present our results from a high-altitude radio frequency measurement campaign with the goal to gain insights about the challenges and limitations of receiving 1090 MHz signals at high altitudes. We used a high-altitude balloon equipped with a software-defined radio to collect 1090 MHz signal data. In an extensive analysis of these data, we identify several challenges and provide a first impression of the radio environment at altitudes up to 33.5 km.
Abstract
Receiving signals on the 1090 MHz frequency, one of the most important radio frequencies used in aviation, is typically done using ground-based receivers. However, an increasing [...]
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Boomerang: Real-Time I/O Meets Legacy Systems
A. Golchin, S. Sinha, R. West

Collection of open conferences in research transport (2019). Vol. 2019, 112

Abstract
This paper presents Boomerang, an I/O system that integrates a legacy non-real-time OS with one that is customized for timing-sensitive tasks. A relatively small RTOS benefits from the pre-existing libraries, drivers and services of the legacy system. Additionally, timing-critical tasks are isolated from less critical tasks by securely partitioning machine resources among the separate OSes. Boomerang guarantees end-to-end processing delays on input data that requires outputs to be generated within specific time bounds. We show how to construct composable task pipelines in Boomerang that combine functionality spanning a custom RTOS and a legacy Linux system. By dedicating time-critical I/O to the RTOS, we ensure that complementary services provided by Linux are sufficiently predictable to meet end-to-end service guarantees. While Boomerang benefits from spatial isolation, it also outperforms a standalone Linux system using deadline-based CPU reservations for pipeline tasks. We also show how Boomerang outperforms a virtualized system called ACRN, designed for automotive systems. Comment: This paper is now accepted for publication in Proceedings of the 26th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), Sydney, Australia, April 21-24, 2020
Abstract
This paper presents Boomerang, an I/O system that integrates a legacy non-real-time OS with one that is customized for timing-sensitive tasks. A relatively small RTOS benefits [...]
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Bodyfitr: Robust Automatic 3D Human Body Fitting
K. Cherenkova, D. Aouada, G. Gusev, A. Shabayek, A. Saint, B. Ottersten

Collection of open conferences in research transport (2019). Vol. 2019, 111

Abstract
This paper proposes BODYFITR, a fully automatic method to fit a human body model to static 3D scans with complex poses. Automatic and reliable 3D human body fitting is necessary for many applications related to healthcare, digital ergonomics, avatar creation and security, especially in industrial contexts for large-scale product design. Existing works either make prior assumptions on the pose, require manual annotation of the data or have difficulty handling complex poses. This work addresses these limitations by providing a novel automatic fitting pipeline with carefully integrated building blocks designed for a systematic and robust approach. It is validated on the 3DBodyTex dataset, with hundreds of high-quality 3D body scans, and shown to outperform prior works in static body pose and shape estimation, qualitatively and quantitatively. The method is also applied to the creation of realistic 3D avatars from the high-quality texture scans of 3DBodyTex, further demonstrating its capabilities.
Abstract
This paper proposes BODYFITR, a fully automatic method to fit a human body model to static 3D scans with complex poses. Automatic and reliable 3D human body fitting is necessary [...]
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TransAID - Transition Areas for Infrastructure-Assisted Driving
J. Schindler

Collection of open conferences in research transport (2019). Vol. 2019, 109
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Optimization of machinery operation modes from the point of view of their dynamics
E. Kalinin, M. Shuliak, I. Koliesnik

Collection of open conferences in research transport (2019). Vol. 2019, 108

Abstract
This paper presents"strong" "/strong"an analysis and synthesis of optimization methods of machinery dynamic modes. Theoretical studies have shown that in order to find optimum, one must define a differential equation describing the motion of the system, which would ensure the most advantageous dynamic regime determined by the stationary value of the corresponding functional. The definition of this equation must be carried out while machinery construction is taking place, as its physical parameters and layout form the basis of these differential equations. Such approach requires the introduction of certain principles significantly affecting the development of optimization methods justified in this paper. To solve the problem of optimal machinery modes, it is more suitable to perform a separation of complex motion by its dynamic properties Suppose that the complex motion can be devided into the motion of the machinery unit as a whole, to the static displacements of its elements as solid bodies, to the increasing and damping components of motion and to the vibrational component. The findings of the study indicate that the most advantageous machinery dynamic mode is determined by the conditions of the technological process, which would ensure its highest productivity, the lowest energy consumption and other optimal technical and economic indicators. This regime corresponds to the motion of the unit as a whole, that is, to the variation in the quasi-cyclic coordinates. The vector of external forces applied to the machinery is reduced to the initial conditions of its motion; homogeneous differential equations are considered further. The fundamental system of their solutions depends on the initial conditions of motion generated by external systems.
Abstract
This paper presents"strong" "/strong"an analysis and synthesis of optimization methods of machinery dynamic modes. Theoretical studies have shown that in order to find optimum, [...]
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A comparison between various pump systems for high flow rate tailings pipelines
H. Krimpenfort

Collection of open conferences in research transport (2019). Vol. 2019, 107

Abstract
Large mines produce tailings in high volumes. As suitable large tailings storage facilities are becoming scarce and difficult to find, tailings need to be transferred over longer distances than before. These longer distances, especially when a high positive static head and an extended transfer length have to be covered, require high discharge pressures. For this purpose, a number of alternative pumping systems are available. The first and most traditional method is to use centrifugal pump systems with multiple pumps in series. Over the last several years however, piston diaphragm pumps have also been successfully used for many such applications, especially at high and very high discharge pressures. Centrifugal pumps installed in series are usually applied at high flow rates at system pressures up to a maximum of 45–55 bar. Piston diaphragm pumps find application at lower flow rates and at pressures above 35 bar. In this paper, a train of centrifugal pumps will be compared with conventional (medium flow rate) piston diaphragm pumps and with high flow rate piston diaphragm pumps, which have recently become available and operate successfully. The comparison is based on an undefined type of tailings at a flow rate of 5,000 m³/hr. The selected discharge pressure is 50 bar, for which traditionally centrifugal pumps are used. This paper will show that at these lower discharge pressures and higher flow rates, piston diaphragm pumps offer a very feasible alternative. All key figures of CAPEX and OPEX parameters are compared, resulting in a payback period calculation, accompanied by a sensitivity calculation with different OPEX parameters. In addition to the commercial differences between the various systems, technical aspects will also be discussed. This paper will show that high-capacity piston diaphragm pumps are the most feasible solution for high-flow tailings applications.
Abstract
Large mines produce tailings in high volumes. As suitable large tailings storage facilities are becoming scarce and difficult to find, tailings need to be transferred over [...]
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Evaluation of the limiting state of the material of trunk gas pipelines
A. Burnashev

Collection of open conferences in research transport (2019). Vol. 2019, 106
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Intrinsic assessment of OpenStreetMap contribution patterns through Exploratory Spatial Data Analysis
M. Minghini, D. Oxoli, F. Frassinelli, M. Brovelli

Collection of open conferences in research transport (2019). Vol. 2019, 105

Abstract
Minghini et al. (2019). Intrinsic assessment of OpenStreetMap contribution patterns through Exploratory Spatial Data Analysis In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 13-14. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3387683
Abstract
Minghini et al. (2019). Intrinsic assessment of OpenStreetMap contribution patterns through Exploratory Spatial Data Analysis In: Minghini, M., Grinberger, A.Y., Juhász, [...]
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Turkey OpenStreetMap Dataset - Spatial Analysis of Development and Growth Proxies
M. Zia, Z. Cakir, D. Seker

Collection of open conferences in research transport (2021). Vol. 2019, 104

Abstract
Number of studies covering major data aspects of OpenStreetMap (OSM) for developed cities and countries are available in scientific literature. However, this is not the case for developing ones mainly because of low data availability in OSM. This study presents a time-series spatial analysis of Turkey OSM dataset, a developing country, between the year 2007 and 2015 to understand how the dataset has developed with time and space. Five different socio-economic factors of the region are tested to find their relationship, if any, with dataset growth. An east-west spatial trend in data density is observed within the country. ''Population Density'' and ''Literacy Level'' of the region are found be the factors controlling it. It has also been observed that the street network of the region has followed the Exploration and Densification evolutionary model. High participation inequality is found within the OSM mappers, with only 5 of them responsible for the country’s 50% geo-data upload. Furthermore, it is found that these mappers use other Volunteered Geographic Information (VGI) and government open-dataset to feed into OSM. This study is believed to bring some high level insights of OSM for a developing country which would be useful for geographers, open-data policy makers, VGI projects planners and data-curators to structure and deploy similar future projects.
Abstract
Number of studies covering major data aspects of OpenStreetMap (OSM) for developed cities and countries are available in scientific literature. However, this is not the case [...]
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[EN-A-37] Coordinated Sequencing of Traffic on Multiple En-route Constraint Points
S. Rapaya, P. Notry, D. Delahaye

Collection of open conferences in research transport (2019). Vol. 2019, 103

Abstract
International audience; Air transportation traffic is progressively increasing over the years and dealing with it is an essential task to guarantee fluid flights in the future. Several works already indexed multiple aspects of aviation, among them, the E-MAN system. It introduced the sequencing of arriving traffic, starting from early stages of the En-route phase. This change facilitated the work for the approach controllers but also increased the workload of the En-route controllers. To handle that workload, controllers are now assisted by tools that consider the new constraints introduced by the arrival management system and propose advisories. From that same perspective, our project focuses on an algorithm for a helper tool that will combine both aspects of traffic sequencing in the En-route phase and conflict resolution. With this novel approach, we automatically generate near-to-optimal flight decisions, given that we can modify the speed and the flight level to respect the sequencing constraints and cut down potential conflicts. We categorize the problem as a mathematical optimization case. Thus, we describe a detailed mathematical model which covers all the aspects of the problem. This model gives a basis for the implementation of the flight optimizer. Later, we propose a solution based on a sliding window simulated annealing algorithm which reduces the complexity and takes into account uncertainties. Finally, we successfully test an implementation of the solution with real-life traffic data. It corresponds to flights within France going towards Paris CDG airport over a period of 24 hours. The results demonstrate a total conflicts resolution with satisfying compliance with sequencing constraints.
Abstract
International audience; Air transportation traffic is progressively increasing over the years and dealing with it is an essential task to guarantee fluid flights in the future. [...]
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Towards Certification of Autonomous Driving: Systematic Test Case Generation for a Comprehensive but Economically-Feasible Assessment of Lane Keeping Assist Algorithms
C. Gnandt, D. Fratzke, T. Ponn, M. Lienkamp

Collection of open conferences in research transport (2019). Vol. 2019, 102

Abstract
utomation of the driving task continues to progress rapidly. In addition to improving the algorithms, proof of their safety is still an unsolved problem. For an automated driving function that does not require permanent monitoring by the driver, a theoretically infinite number of possible traffic situations must be tested. One promising method to overcome this problem is the scenario-based approach. This approach shall enable an economic certification of automated driving functions with sufficient test space coverage. However, even with this approach, the selection of the scenarios to be tested is still problematic. The first step is to consider a driver assistance system in order to reduce complexity. For the Lane Keeping Assist System under consideration, this paper defines a methodology as well as the scenarios for a comprehensive yet economically-feasible certification. Economical-feasibility of the presented methodology is shown in the results by an approximation of the resulting simulation costs for executing the defined test cases.
Abstract
utomation of the driving task continues to progress rapidly. In addition to improving the algorithms, proof of their safety is still an unsolved problem. For an automated [...]
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Formation of transport-logistic clusters in Ukraine
S. Sharai, M. Roі, D. Dekhtiarenko

Collection of open conferences in research transport (2019). Vol. 2019, 100

Abstract
Transport play an important role in the development of the economy. For efficient functioning of the transport system there should be not only high technical conditions of rolling stock, but also a developed transport infrastructure. The geographic position of Ukraine makes it a promising transit state. The purpose if this paper is to present the results of the research on the Ukrainian transport-logistic infrastructure. Since transport is one of the main components of economic development, it is relevant to study this sector of the economy and identify prospective directions for improvement, namely the formation of Transport-Logistics Clusters (TLC) in Ukraine. As a result of the research, it has been found that in Ukraine there are priority terrestrial modes of transport in comparison with other types. The value of the research is that having analyzed the experience of other countries in the establishment of TLC, the authors have identified the benefits of different cluster strategies for the formation of TLCs in Ukraine.
Abstract
Transport play an important role in the development of the economy. For efficient functioning of the transport system there should be not only high technical conditions of [...]
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An Air Traffic Management Data Traffic Pattern for Aeronautical Communication System Evaluations
T. Graupl, N. Maurer

Collection of open conferences in research transport (2019). Vol. 2019, 99

Abstract
Modern air traffic management relies on a communication infrastructure increasingly suffering from the VHF band’s growing saturation in high density areas. Air traffic management communication shall therefore transition from analog VHF voice communication to more spectrum efficient digital data communication. These proposed digital technologies have to be evaluated carefully against the expected data traffic to ascertain that they offer the required capacity and performance. This paper describes the characteristics of air traffic management data and a method to generate a data traffic pattern suitable as input for the performance evaluation of digital aeronautical data communication systems. The data traffic pattern is derived from large scale computer simulations. Based on the simulation results, the paper provides guidance on how to model a data traffic pattern that is directly usable for practitioners wishing to evaluate the performance of aeronautical data communication systems.
Abstract
Modern air traffic management relies on a communication infrastructure increasingly suffering from the VHF band’s growing saturation in high density areas. Air traffic management [...]
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Dual Averaging Method for Online Graph-structured Sparsity
Y. Ying, B. Zhou, F. Chen

Collection of open conferences in research transport (2019). Vol. 2019, 98

Abstract
Online learning algorithms update models via one sample per iteration, thus efficient to process large-scale datasets and useful to detect malicious events for social benefits, such as disease outbreak and traffic congestion on the fly. However, existing algorithms for graph-structured models focused on the offline setting and the least square loss, incapable for online setting, while methods designed for online setting cannot be directly applied to the problem of complex (usually non-convex) graph-structured sparsity model. To address these limitations, in this paper we propose a new algorithm for graph-structured sparsity constraint problems under online setting, which we call \\textsc{GraphDA}. The key part in \\textsc{GraphDA} is to project both averaging gradient (in dual space) and primal variables (in primal space) onto lower dimensional subspaces, thus capturing the graph-structured sparsity effectively. Furthermore, the objective functions assumed here are generally convex so as to handle different losses for online learning settings. To the best of our knowledge, \\textsc{GraphDA} is the first online learning algorithm for graph-structure constrained optimization problems. To validate our method, we conduct extensive experiments on both benchmark graph and real-world graph datasets. Our experiment results show that, compared to other baseline methods, \\textsc{GraphDA} not only improves classification performance, but also successfully captures graph-structured features more effectively, hence stronger interpretability. Comment: 11 pages, 14 figure
Abstract
Online learning algorithms update models via one sample per iteration, thus efficient to process large-scale datasets and useful to detect malicious events for social benefits, [...]
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A Machine Learning Approach for Conflict Resolution in Dense Traffic Scenarios with Uncertainties
D. Pham, N. Tran, S. Alam, V. Duong, D. Delahaye

Collection of open conferences in research transport (2019). Vol. 2019, 97

Abstract
International audience; With the continuous growth in the air transportation demand, air traffic controllers will have to handle increased traffic and consequently more potential conflicts. That gives rise to the need for conflict resolution tools that can perform well in high-density traffic scenarios given a noisy environment. Unlike model-based approaches, learning-based or machine learning approaches can take advantage of historical traffic data and flexibly encapsulate the environmental uncertainty. In this study, we propose an artificial intelligent agent that is capable of resolving conflicts, in the presence of traffic and given uncertainties in conflict resolution maneuvers, without the need of prior knowledge about a set of rules mapping from conflict scenarios to expected actions. The conflict resolution task is formulated as a decision-making problem in large and complex action space, which is applicable for employing the reinforcement learning algorithm. Our work includes the development of a learning environment, scenario state representation, reward function, and learning algorithm. As a result, the proposed method, inspired from Deep Q-learning and Deep Deterministic Policy Gradient algorithms, can resolve conflicts, with a success rate of over 81%, in the presence of traffic and varying degrees of uncertainties.
Abstract
International audience; With the continuous growth in the air transportation demand, air traffic controllers will have to handle increased traffic and consequently more potential [...]
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Key progress on the filling mining of deep resources in Jinchuan Nickel Deposit
Z. Yang

Collection of open conferences in research transport (2019). Vol. 2019, 96

Abstract
On the basis of resource endowment and geological features, harsh geological conditions and mining environment for the effective mining and comprehensive utilization of deep resources in Jinchuan Nickel Deposit were systematically analyzed, including high stress, fragmentized ore rock, prevalent deformation, difficult support, complicated rock mechanics and low mining recovery. An integrated technology package has been established for safe, efficient and continuous mining at the huge, complex and deep nickel and cobalt mine by proposing a large-area continuous mining method with honeycomb drives and establishing ground control theory and technology package in high stress and fragmented ore rock, and by developing new backfilling cement material and deep backfilling technology with pipeline transport of high density slurry with coarse aggregate, in order for an efficient exploitation and comprehensive utilization of deep resources in Jinchuan Nickel Mine, hence presenting technological demonstration for the underground mine using cemented undercut-and-fill mining method with stressful, fragmented and rheological rock.
Abstract
On the basis of resource endowment and geological features, harsh geological conditions and mining environment for the effective mining and comprehensive utilization of deep [...]
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Database-supported change analysis and quality evaluation of OpenStreetMap Data
M. Breunig, P. Kuper, A. Martini

Collection of open conferences in research transport (2019). Vol. 2019, 95

Abstract
Abstract. A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and to compare the changes between new and old versions of the same area. This paper first introduces into a differentiated classification of changes on OpenStreetMap data sets. Then a methodology for an automated database-supported analysis of changes is presented. Beyond the information already provided from the OpenStreetMap server, we present a more detailed analysis with derived information. Based on this approach it is possible to identify objects with attributive or geometric changes and to find out how they exactly differ from their previous versions. The analysis shows in which regions mappers were active during a certain time interval. Furthermore, a time based approach based on various parameters to determine the quality of the data is presented. It provides a guideline of data quality and works without any reference data. Therefore, an indication about the development of OpenStreetMap in terms of completeness and correctness of the data in different regions is given. Finally, a conclusion and an outlook on open research questions are presented. Document type: Article
Abstract
Abstract. A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and [...]
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Impact of Electric Vehicle Charging Infrastructure Expansion on Microgrid Economics: A Case Study
M. Sprengeler, R. Popova, H. Nguyen, T. Freudenmacher, G. Stryi-Hipp, M. Rotta

Collection of open conferences in research transport (2020). Vol. 2020, 28

Abstract
The operation of public and semi-public charging infrastructure is often not profitable yet. However, the integration of charging infrastructure in microgrids enables the introduction of innovative business models, e.g. by local renewable energy generation and storage units. Another driver to improve profitability is to adapt the charging infrastructure expansion according to its usage characteristics. This study presents a method to optimize the charging infrastructure expansion. Therefore, a mixed integer linear program with the aim to minimize costs is formulated and applied on real-world data. Via the optimization, different scenarios are developed and the microgrid integration is simulated in an operation optimization algorithm. Different business models such as PV and battery storage integration are computed and the economics of the business models in the different scenarios are evaluated. It can be concluded that microgrid integration can be a significant driver of charging infrastructure operation profitability. Integrating PV generation shortens the payback period in all scenarios. Also, PV generation and battery storage combined improve profitability, but not to the same extent than without storage unit. Furthermore, the optimization of the charging infrastructure expansion leads to a significant improvement of profitability. Combining both the microgrid integration, as well as the expansion optimization, the payback period can be decreased by up until 67 %.
Abstract
The operation of public and semi-public charging infrastructure is often not profitable yet. However, the integration of charging infrastructure in microgrids enables the [...]
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Regret Minimisation and System-Efficiency in Route Choice
B. Silva, A. Bazzan, G. Ramos

Collection of open conferences in research transport (2019). Vol. 2019, 93

Abstract
Traffic congestions present a major challenge in large cities. Consid- ering the distributed, self-interested nature oftraffic we tackle congestions using multiagent reinforcement learning (MARL). In this thesis, we advance the state- of-the-art by delivering the first MARL convergence guarantees in congestion- like problems. We introduce an algorithm through which drivers can learn opti- mal routes by locally estimating the regret associated with their decisions, which we prove to converge to an equilibrium. In order to mitigate the effects ofselfish- ness, we also devise a decentralised tolling scheme, which we prove to minimise traffic congestion levels. Our theoretical results are supported by an extensive empirical evaluation on realistic traffic networks. 1.
Abstract
Traffic congestions present a major challenge in large cities. Consid- ering the distributed, self-interested nature oftraffic we tackle congestions using multiagent reinforcement [...]
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Demagnetization analysis of an open-end windings 5-phase PMSM under transistor short-circuit fault
E. Semail, T. Moraes, N. Nguyen

Collection of open conferences in research transport (2019). Vol. 2019, 92

Abstract
For an open-end windings integrated Permanent Magnet Synchronous Machine, the demagnetization of the permanent magnets is analyzed when a transistor is short-circuited and no specific control strategy is adopted. Depending on the temperature, the high currents due to the inverter fault may locally demagnetized the permanent magnets leading to an accelerated aging of the machine and torque loss. A co-simulation, using a Finite Element software for the machine coupled with an average modeling of the transistor, gives interesting local prediction of the machine behavior in healthy and degraded mode. This work has been achieved within the framework of CE2I project. CE2I is co-financed by European Union with the financial support of European Regional Development Fund (ERDF), French State and the French Region of Hauts-de-France.
Abstract
For an open-end windings integrated Permanent Magnet Synchronous Machine, the demagnetization of the permanent magnets is analyzed when a transistor is short-circuited and [...]
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From Shared electric Mobility Providers (SeMPs) to electric Mobility as a Service (eMaaS) players: A first approach to assess the Technical Level of Integration of Mobility Service Providers’ functionalities applied to the European (e)MaaS market
J. Reyes Garcia, M. Westerhof, S. Haveman, G. Bonnema

Collection of open conferences in research transport (2019). Vol. 2019, 91

Abstract
In this paper we present an approach to evaluate to what extent Mobility Service Providers (MSPs) can be considered (e)MaaS players. Following that approach, we conduct an analysis of 128 MSPs, specifically Shared electric Mobility Providers (SeMPs), currently operating in the European market. The goal of the analysis is twofold. Firstly, it aims at demonstrating the applicability of the proposed approach. Secondly, it aims at offering an overview of the current state of the market concerning the Technical Level of Inte- gration (TLI) of European SeMPs. Our results show that, on the one hand, most of the SeMPs currently operating in Europe have a medium to high TLI. However, those levels are mostly not applicable for multi- modal (i.e. for multiple modes of transport or multiple MSPs) interfaces but for single-mode interfaces. On the other hand, our results also show that there are already some SeMPs in the current European market that have fully integrated functionalities, in that case, SeMPs mostly have multimodal interfaces. Based on the analysis and discussion presented in this paper, we concluded that the TLI approach offers an effective technique to determine, and easily visualize, the level of integration of the technical functionalities of MSPs.
Abstract
In this paper we present an approach to evaluate to what extent Mobility Service Providers (MSPs) can be considered (e)MaaS players. Following that approach, we conduct an [...]
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Mobility Impacts of Automated Driving and Shared Mobility: Explorative Model and Case Study of the Province of North-Holland
M. Snelder, I. Wilmink, J. van der Gun, H. Bergveld, P. Hoseini, B. van Arem

Collection of open conferences in research transport (2019). Vol. 2019, 90

Abstract
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of the author’s knowledge, it is the first model that combines a network fundamental diagram with choice models. A second contribution is the inclusion of automated vehicles, automated (shared) taxis, automated shared vans and new parking concepts in the model as well as the way in which they affect mobility choices and traffic conditions. The insights into the impact mechanisms and the direct and indirect mobility impacts are the third contribution. The short computation time of the model enables exploration of large numbers of scenarios, sensitivity analyses and assessments of the impacts of interventions. The model was applied tin a case study of the Dutch Province of North-Holland, in which the potential impacts of automated and shared vehicles and mitigating interventions were explored. In this case study, four extreme scenarios were explored, in which 100% of the vehicles have SAE-level 3/4 or 5 and people have a low or high willingness to share. The extremes were chosen to get insights into maximum effects. The results show that if automated vehicles and sharing are accepted, it is likely that there will be considerable changes in mobility patterns and traffic performance, with both positive and problematic effects.
Abstract
This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model [...]
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Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP
S. Almpani, I. Ouranos, P. Frangos, P. Stefaneas, T. Mitsikas, J. Vennekens, M. Deryck, H. Boley

Collection of open conferences in research transport (2019). Vol. 2019, 89

Abstract
This paper studies Knowledge Bases (KBs) in PSOA RuleML and IDP, aligning, interoperating, and co-executing them for a use case of Air Traffic Control (ATC) regulations. We focus on the common core of facts and rules in both languages, explaining basic language features. The used knowledge sources are regulations specified in (legal) English, and an aircraft data schema. In the modeling process, inconsistencies in both sources were discovered. We present the discovery process utilizing both specification languages, and highlight their unique features. We introduce three extensions to this ATC KB core: (1) While the current PSOA RuleML does not distinguish the ontology separately from the instance level, IDP does. Hence, we specify a vocabulary-enriched version of ATC KB in IDP for knowledge validation. (2) While the current IDP uses relational modeling, PSOA additionally supports graph modeling. Hence, we specify a relationally interoperable graph version of ATC KB in PSOA. (3) The KB is extended to include optimization criteria to allow the determination of an optimal sequence of more than two aircraft.
Abstract
This paper studies Knowledge Bases (KBs) in PSOA RuleML and IDP, aligning, interoperating, and co-executing them for a use case of Air Traffic Control (ATC) regulations. We [...]
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A Simulation Framework For Fast Design Space Exploration Of Unmanned Air System Traffic Management Policies
J. Zhao, C. Caicedo, Q. Qiu, F. Basti, M. Gursoy, C. Luo, Z. Zhao

Collection of open conferences in research transport (2019). Vol. 2019, 88

Abstract
The number of daily small Unmanned Aircraft Systems (sUAS) operations in uncontrolled low altitude airspace is expected to reach into the millions. UAS Traffic Management (UTM) is an emerging concept aiming at the safe and efficient management of such very dense traffic, but few studies are addressing the policies to accommodate such demand and the required ground infrastructure in suburban or urban environments. Searching for the optimal air traffic management policy is a combinatorial optimization problem with intractable complexity when the number of sUAS and the constraints increases. As the demands on the airspace increase and traffic patterns get complicated, it is difficult to forecast the potential low altitude airspace hotspots and the corresponding ground resource requirements. This work presents a Multi-agent Air Traffic and Resource Usage Simulation (MATRUS) framework that aims for fast evaluation of different air traffic management policies and the relationship between policy, environment and resulting traffic patterns. It can also be used as a tool to decide the resource distribution and launch site location in the planning of a next-generation smart city. As a case study, detailed comparisons are provided for the sUAS flight time, conflict ratio, cellular communication resource usage, for a managed (centrally coordinated) and unmanaged (free flight) traffic scenario. Comment: The Integrated Communications Navigation and Surveillance (ICNS) Conference in 2019
Abstract
The number of daily small Unmanned Aircraft Systems (sUAS) operations in uncontrolled low altitude airspace is expected to reach into the millions. UAS Traffic Management [...]
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Interdependent Uncertainty Handling in Trajectory Prediction
H. Fricke, J. Rosenow, T. Zeh

Collection of open conferences in research transport (2019). Vol. 2019, 87

Abstract
The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties have to be modeled properly and considered in decision support tools for efficient air traffic flow management. Therefore, the subjacent causes for uncertainties, their effects on the aircraft trajectory and their dependencies to each other must be understood in detail. Besides the atmospheric conditions as the main external cause, the aircraft itself induces uncertainties to its trajectory. In this study, a cause-and-effect model is introduced, which deals with multiple interdependent uncertainties with different stochastic behavior and their impact on trajectory prediction. The approach is applied to typical uncertainties in trajectory prediction, such as the actual take-off mass, non-constant true air speeds, and uncertain weather conditions. The continuous climb profiles of those disturbed trajectories are successfully predicted. In general, our approach is applicable to all sources of quantifiable interdependent uncertainties. Therewith, ground-based trajectory prediction can be improved and a successful implementation of trajectory-based operations in the European air traffic system can be advanced. Document type: Article
Abstract
The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the [...]
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Policy Optimization in Automated Point Merge Trajectory Planning: An Artificial Intelligence-based Approach
M. Liang, P. Notry, W. Li, D. Delahaye

Collection of open conferences in research transport (2019). Vol. 2019, 86

Abstract
Traffic Management (ATM) is a complex decision-making process. Air traffic controllers’ decision on aircraft trajectory control actions directly leads to the efficiency of traffic flow management. In the Automated Point Merge Trajectory Planning (APMTP) problem, it aims to realize an automated routine trajectory management in Terminal Manoeuvring Area (TMA) with an intelligent decision-making agent.An Artificial Intelligence-based approach, mainly Reinforcement Learning (RL) algorithm, is applied to adaptively and smartly integrate four types of de-conflict actions for solving conflicts with fewer delays on the environment. In this paper, we will mainly discuss the policy optimization in APMTP, focus on improving the agent’s learning quality and exploration efficiency. Firstly,application of RL in adaptive trajectory planning is presented.APMTP problem is adaptively divided into several sub-problems.For each sub-problem, an online policy π is applied to guide the simulation and optimization modules to find out the conflict free and less-delay solution. The online policy π is a scale of weight distribution for choosing desirable actions. It follows the rule of Roulette-wheel selection with weighted probability. The highest desirable decision variable has the largest share of the roulette wheel, while the lowest desirable decision variable has the smallest share of the roulette wheel. The RL direct policy optimization algorithm is designed to update the online policy π.Finally, experiments are built up for validation of the proposed policy optimization algorithm for the intelligent decision-making in APMTP. The results in the test environment show that learning agent with different exploration and exploitation ability will result in different system performance in conflict resolution and delay Refereed/Peer-reviewed
Abstract
Traffic Management (ATM) is a complex decision-making process. Air traffic controllers’ decision on aircraft trajectory control actions directly leads to the efficiency [...]
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Assessing the Completeness of Urban Green Spaces in OpenStreetMap
C. Ludwig, R. Hecht, S. Lautenbach, M. Schorcht, A. Zipf

Collection of open conferences in research transport (2019). Vol. 2019, 83

Abstract
Ludwig et al. (2019). Assessing the Completeness of Urban Green Spaces in OpenStreetMap In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 21-22. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3387701
Abstract
Ludwig et al. (2019). Assessing the Completeness of Urban Green Spaces in OpenStreetMap In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings [...]
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SPONGE: Software-Defined Traffic Engineering to Absorb Influx of Network Traffic
S. Chowdhury, J. Francois, R. Boutaba, B. Henry, A. Lahmadi, R. Azaïs

Collection of open conferences in research transport (2019). Vol. 2019, 82

Abstract
International audience; Existing shortest path-based routing in wide area networks or equal cost multi-path routing in data center networks do not consider the load on the links while taking routing decisions. As a consequence, an influx of network traffic stemming from events such as distributed link flooding attacks and data shuffle during large scale analytics can congest network links despite the network having sufficient capacity on alternate paths to absorb the traffic. This can have several negative consequences, service unavailability, delayed flow completion, packet losses, among others. In this regard, we propose SPONGE, a traffic engineering mechanism for handling sudden influx of network traffic. SPONGE models the network as a stochastic process, takes the switch queue occupancy and traffic rate as inputs, and leverages the multiple available paths in the network to route traffic in a way that minimizes the overall packet loss in the network. We demonstrate the practicality of SPONGE through an OpenFlow based implementation, where we periodically and pro-actively reroute network traffic to the routes computed by SPONGE. Mininet emulations using real network topologies show that SPONGE is capable of reducing packet drops by 20% on average even when the network is highly loaded because of an ongoing link flooding attack.
Abstract
International audience; Existing shortest path-based routing in wide area networks or equal cost multi-path routing in data center networks do not consider the load on the [...]
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Automated Longitudinal Control Based on Nonlinear Recursive B-Spline Approximation for Battery Electric Vehicles
J. Jauch, F. Bleimund, M. Frey, F. Gauterin

Collection of open conferences in research transport (2021). Vol. 2019, 80

Abstract
This works presents a driver assistance system for energy-efficient automated longitudinal control (ALC) of a battery electric vehicle (BEV). The ALC calculates a temporal velocity trajectory from map data. The trajectory is represented by a cubic B-spline function and results from an optimization problem with respect to travel time, driving comfort and energy consumption. For the energetic optimization we propose an adaptive model of the required electrical traction power. The simple power train of a BEV allows the formulation of constraints as soft constraints. This leads to an unconstrained optimization problem that can be solved with iterative filter-based data approximation algorithms. The result is a direct trajectory optimization method of which the effort grows linearly with the trajectory length, as opposed to exponentially as with most other direct methods. We evaluate ALC in real test drives with a BEV. We also investigate the energy-saving potential in driving simulations with ALC compared to manual longitudinal control (MLC). On the chosen reference route the ALC saves up to 3.4% energy compared to MLC at same average velocity, and achieves a 2.6% higher average velocity than MLC at the same energy consumption.
Abstract
This works presents a driver assistance system for energy-efficient automated longitudinal control (ALC) of a battery electric vehicle (BEV). The ALC calculates a temporal [...]
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Analysis of OSM data through OSM-Notes user posting
T. Seto, H. Kanasugi, Y. Nishimura

Collection of open conferences in research transport (2019). Vol. 2019, 79

Abstract
Seto et al. (2019). Analysis of OSM data through OSM-Notes user posting In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 15-16. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3387685
Abstract
Seto et al. (2019). Analysis of OSM data through OSM-Notes user posting In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the [...]
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Revisiting Subnet Inference WISE-ly
J. Grailet, B. Donnet

Collection of open conferences in research transport (2019). Vol. 2019, 78

Abstract
Since the late 90’s, the Internet topology discovery has been an attractive and important research topic, leading, among others, to multiple probing and data analysis tools developed by the research community. This paper looks at the particular problem of discovering subnets (i.e., a set of devices that are located on the same connection medium and that can communicate directly with each other at the link layer). In this paper, we first show that the use of traffic engineering policies may increase the difficulty of subnet inference. We carefully characterize those difficulties and quantify their prevalence in the wild. Next, we introduce WISE (Wide and lInear Subnet inferencE), a novel tool for subnet inference designed to deal with those issues and able to discover subnets on wide ranges of IP addresses in a linear time. Using two groundtruth networks, we demonstrate that WISE performs better than state-of-the-art tools while being competitive in terms of subnet accuracy. We also show, through large-scale measurements, that the selection of vantage point with WISE does not matter in terms of subnet accuracy. Finally, all our code (WISE, data processing, results plotting) and collected data are freely available. Peer reviewed
Abstract
Since the late 90’s, the Internet topology discovery has been an attractive and important research topic, leading, among others, to multiple probing and data analysis tools [...]
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Estimating Configuration Parameters of Pipelines for Accelerating N-Body Simulations with an FPGA using High-level Synthesis
A. Muramatsu, T. Narumi

Collection of open conferences in research transport (2019). Vol. 2019, 76

Abstract
In the era of the IoT (Internet of Things) and Edge computing, SoC (System on Chip) with an FPGA (Field Programmable Gate Array) is a suitable solution for embedded systems because it supports running rich operating systems on general-purpose CPUs, as well as the FPGA’s acceleration for specific computing. One problem of designing an accelerator on an FPGA is that optimization of the logic for the accelerator is not automatic and much trial and error is needed before attaining peak performance from the SoC. In this paper we propose a method to reduce the development time of the accelerator using N-body simulation as a target application. Based on the hardware resources needed for several pipelines of the accelerator and their performance estimation model, we can estimate how many pipelines can be implemented on an SoC. In addition, the amount of memory each pipeline requires for attaining maximum performance is suggested. Our model agreed with the actual calculation speed for different constraining conditions.
Abstract
In the era of the IoT (Internet of Things) and Edge computing, SoC (System on Chip) with an FPGA (Field Programmable Gate Array) is a suitable solution for embedded systems [...]
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Collaborative Exchange of Cargo Truck Loads: Approaches to Reducing Empty Trucks in Logistics Chains
H. Hvolby, P. Turner, M. Neagoe, S. Vestergaard, K. Steger-Jensen

Collection of open conferences in research transport (2019). Vol. 2019, 74

Abstract
Part 1: Smart Supply Networks; International audience; Reducing the volume of trucks carrying empty or below capacity loads on road networks are both socio-economic and environmental sustainability issues for the logistics industry. Planning concepts for a collaborative logistics exchange based on real-time data are described as well as the benefits in terms of optimizing load capacity utilization, minimization of empty running, reducing costs, traffic congestion, and truck emissions. Document type: Conference object
Abstract
Part 1: Smart Supply Networks; International audience; Reducing the volume of trucks carrying empty or below capacity loads on road networks are both socio-economic and environmental [...]
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Comparative Analysis of Vehicle-to-Vehicle (V2V) Power Transfer Configurations without Additional Power Converters
D. Pedrosa, T. Sousa, C. Martins, V. Monteiro, J. Afonso, L. Machado

Collection of open conferences in research transport (2020). Vol. 2020, 25

Abstract
This paper presents a comparative analysis of power transfer configurations towards vehicle-to-vehicle (V2V) battery charging operation without using additional power converters, i.e., using just the on-board battery chargers of two electric vehicles (EVs). Three access interfaces were considered, namely the ac power grid interface, the dc-link interface and the dc battery interface, which allow the establishment of eight V2V configurations. The defined configurations are described and verified through computational simulations. A comparison is performed based on quantitative data, i.e., power transfer efficiency for a given output power range, and qualitative data, i.e., flexibility and safety. According to the obtained results, it can be concluded that each V2V configuration has its pros and cons regarding efficiency, number of possible quadrant operation and need for additional equipment. This work has been supported by FCT –Fundação para a Ciência e Tecnologiawith-in the Project Scope: UID/CEC/00319/2019. This work has been supported by the FCT Project DAIPESEV PTDC/EEI-EEE/30382/2017, and by FCTProject new-ERA4GRIDs PTDC/EEI-EEE/30283/2017. Mr. Tiago J. C. Sousa is supported by the doctoral scholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agency.
Abstract
This paper presents a comparative analysis of power transfer configurations towards vehicle-to-vehicle (V2V) battery charging operation without using additional power converters, [...]
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When Air Traffic Management Meets Blockchain Technology: a Blockchain-based concept for securing the sharing of Flight Data
N. Larrieu, E. Lochin, H. Asghar, M. Clementi, M. Kaafar

Collection of open conferences in research transport (2019). Vol. 2019, 73

Abstract
The Aviation Industry has been booming for several decades and is expected to keep growing in the future. Therefore, Air Traffic Management (ATM) tools are likely to be soon overwhelmed by the demand. The Single European Sky ATM Research Program (SESAR) 2020, controlled by EUROCONTROL, intends to revisit the management of aeronautical information along its full lifecycle and across the whole European ATM system. The efficient sharing of information over large scale Cyber Physical Systems (CPSs) is a non-trivial problem that raises several challenges including data lineage, data consistency, access rights management and privacy-preservation. Part of the SESAR initiative, System-Wide Information Management (SWIM) project defines standards to enhance the security of aeronautical data shared among stakeholders. Most of its propositions include centralized or partially centralized mechanisms in order to enforce data confidentiality, and privacy. In this paper, we intend to discuss how blockchains can improve the sharing of sensitive data over the ATM system. More specifically, we use the example of flight data and describe a high-level Blockchain-based concept that mimics the decentralized nature of existing A TM system to provide a reliable, distributed storage platform for flight information.
Abstract
The Aviation Industry has been booming for several decades and is expected to keep growing in the future. Therefore, Air Traffic Management (ATM) tools are likely to be soon [...]
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Dead-lock in the introduction of ERS-systems - a case of true uncertainty
B. Hasselgren, F. Widegren

Collection of open conferences in research transport (2020). Vol. 2020, 24

Abstract
a major contributor to reaching the goals of de-carbonization of the transport sector, the introduction of ERS-systems for heavy vehicles is a prioritized action, with Sweden as an example. Even if de-carbonization is asked for by policymakers, and part of the medium to long term strategy for many transport market players, it is very difficult to get the transition to take off. Hindrances related to current roles on the market, regulation and the ability to find new ways to finance and foster new business models can be observed. This resembles a ‘true uncertainty’-situation. The result might be a dead-lock where the introduction of ERS-systems is delayed. It is argued here that platforms and frameworks for testing new systems, where “regimes” supporting shared risk mitigation, faster innovation, and deployment of ERS-technology could be supported. We discuss possible ways for establishing such platforms and crucial policy content for these.
Abstract
a major contributor to reaching the goals of de-carbonization of the transport sector, the introduction of ERS-systems for heavy vehicles is a prioritized action, with Sweden [...]
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Integrated Maintenance and Service Policies Definition for Urban Ropeway Transport System
N. Rezg, O. Bistorin, R. Martinod, L. Castaneda

Collection of open conferences in research transport (2019). Vol. 2019, 72

Abstract
International audience; This work proposes a stochastic model for integrating service and maintenance policies in order to address the queuing problem and the cost of maintenance for public transport systems. The authors adopt the following approaches: (i) a cost-model that considers the uncertainty of passengers’ plans to compute the waiting time; (ii) a maintenance cost-model which take into account two different maintenance policies (periodic block-type and age-based); and (iii) a bi-objective optimisation process to bring together the service and maintenance policies. Finally, the proposed work is applied to a massive-urban ropeway belonging to a public transportation system, in which the current service policy has been evaluated, considering the established transportation operation.
Abstract
International audience; This work proposes a stochastic model for integrating service and maintenance policies in order to address the queuing problem and the cost of maintenance [...]
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Paste backfill system design and commissioning at Chambishi Copper Mine
L. Xiaohui, Y. Wang, X. Miao, A. Wu, Z. Jinjun, C. Wang

Collection of open conferences in research transport (2019). Vol. 2019, 71

Abstract
West orebody is now the main production zone of Chambishi Copper Mine. Upward drift stoping is performed to meet the annual ore production of more than 1 Mt. Cemented classified tailings backfill was originally employed, which then proved to be both economically and operationally impractical due to high cement cost, low metal recovery, severe backfill tailings shortage, etc. As an alternative, the current paste backfill system with low cement addition was suggested after a comprehensive study and investigation. Construction work of the paste backfill system started in 2012. The system was put into production at the beginning of 2014 after commissioning. During commissioning, the backfill system reached a capacity of 60 m3/h with the paste concentration of 68 to 70%, and the friction loss of the pipeline transport was 4-6 MPa/km. To meet the backfill strength, the cement to tailings ratio for primary stopes was 1:12, and 1:30 for secondary stopes. As a result, the composite cost for backfill was only USD 15 to 20 /m3, while ore recovery increased by 35% and mining to cutting ratio dropped by 80 m3/kt. Since commissioning investigations indicate that this paste backfill system will be capable of prolonging west orebody’s service by about 10 years, and will bring about enormous economic returns. This paper presents the case study of the highly automated system and its commissioning performance, with emphasis on key processes including unclassified tailings thickening, two-stage slurry mixing, paste pumping, and underground backfill.
Abstract
West orebody is now the main production zone of Chambishi Copper Mine. Upward drift stoping is performed to meet the annual ore production of more than 1 Mt. Cemented classified [...]
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Improvement of the method for assessing the energy load of vehicle
M. Podrigalo, Y. Tarasov, D. Abramov, M. Kholodov

Collection of open conferences in research transport (2019). Vol. 2019, 70

Abstract
The aim of the research is to improve the indicators assessment accuracy of the vehicle energy load by improving the method of experimentally - theoretical determination of the aerodynamic drag parameters of vehicle in motion. To achieve this goal, it is necessary to solve the problem of determining the dependence of the energy load level on vehicle speed with varying frontal aerodynamic drag coefficient. Studies carried out to clarify the calculation of the parameters of vehicle aerodynamic drag in motion made it possible to determine the correlation between the actual effective engine capacity and the maximum kinetic energy of vehicle at translational motion. When determining the vehicle aerodynamic drag, the constant coefficient of aerodynamic drag is used depending on the speed in all range of vehicle speeds. This leads to significant mistakes in determining the necessary engine capacity expendable to overcome the aerodynamic drag, and vehicle fuel consumption. As a result of the research, analytical expressions, allowing to take into account additional energy losses and correlation between the kinetic energy of the vehicle steady motion and the effective engine capacity have been obtained. The theoretical contribution of the research is that the correlation coefficient between the kinetic energy of vehicle in motion and the effective engine capacity – have been proposed. Studies have shown that if speed of vehicle increases the indicator will monotonously decrease in the range of actual speeds.
Abstract
The aim of the research is to improve the indicators assessment accuracy of the vehicle energy load by improving the method of experimentally - theoretical determination of [...]
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Coordination of Power and Natural Gas Systems: Convexification Approaches for Linepack Modeling
C. Ordoudis, J. Kazempour, P. Pinson, A. Schwele

Collection of open conferences in research transport (2020). Vol. 2020, 23

Abstract
Utilizing operational flexibility from natural gas networks can foster the integration of uncertain and variable renewable power production. We model a combined power and natural gas dispatch to reveal the maximum potential of linepack, i.e., energy storage in the pipelines, as a source of flexibility for the power system. The natural gas flow dynamics are approximated by a combination of steady-state equations and varying incoming and outgoing flows in the pipelines to account for both natural gas transport and linepack. This steady-state natural gas flow results in a nonlinear and nonconvex formulation. To cope with the computational challenges, we explore convex quadratic relaxations and linear approximations. We propose a novel mixed-integer second-order cone formulation including McCormick relaxations to model the bidirectional natural gas flow accounting for linepack. Flexibility is quantified in terms of system cost compared to a dispatch model that either neglects linepack or assumes infinite storage capability.
Abstract
Utilizing operational flexibility from natural gas networks can foster the integration of uncertain and variable renewable power production. We model a combined power and [...]
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Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking
Z. Liu, E. Heiden, G. Sukhatme, R. Ramachandran

Collection of open conferences in research transport (2019). Vol. 2019, 69

Abstract
Light Detection and Ranging (LIDAR) sensors play an important role in the perception stack of autonomous robots, supplying mapping and localization pipelines with depth measurements of the environment. While their accuracy outperforms other types of depth sensors, such as stereo or time-of-flight cameras, the accurate modeling of LIDAR sensors requires laborious manual calibration that typically does not take into account the interaction of laser light with different surface types, incidence angles and other phenomena that significantly influence measurements. In this work, we introduce a physically plausible model of a 2D continuous-wave LIDAR that accounts for the surface-light interactions and simulates the measurement process in the Hokuyo URG-04LX LIDAR. Through automatic differentiation, we employ gradient-based optimization to estimate model parameters from real sensor measurements. Comment: Published at ICRA 2020
Abstract
Light Detection and Ranging (LIDAR) sensors play an important role in the perception stack of autonomous robots, supplying mapping and localization pipelines with depth measurements [...]
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Modeling of assessment of reliability transport systems
Y. Tkhoruk, O. Kucher, M. Holotiuk, M. Krystopchuk, O. Tson, T. Olejarz

Collection of open conferences in research transport (2019). Vol. 2019, 68

Abstract
This article presents results of a study based on the analysis of the development of the theory of reliability whose indicators are formulated indicators of transport systems reliability and contributed to building a system of factors determining their reliability. It is established that the formation of the theory of reliability of transport systems today is not completed. Based on the specifics of the systems, new reliability indicators were proposed and substantiated such as emergency downtime and reliability of emergency downtime. On the basis of the performed studies, it was found that the specifics of the transport process require the introduction of emergency downtime close to the recovery time and the reliability of emergency downtime. It is necessary to introduce two close parameters such as the average recovery time and the average emergency idle time. They are associated with the need to distinguish between the idle time of a technological system, or a separate element when a failure occurs, and the idle time that is needed. For the technological links of the transport system, the main purpose of which is to ensure efficient operation transport process, the probability of emergency downtime can serve as a criterion for assessing their reliability.
Abstract
This article presents results of a study based on the analysis of the development of the theory of reliability whose indicators are formulated indicators of transport systems [...]
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A shipping simulation through pathfinding: SEL within the MSP Challenge simulation platform
P. de Groot, W. Boode, C. Pereira Santos, H. Warmelink, I. Mayer

Collection of open conferences in research transport (2019). Vol. 2019, 67

Abstract
The authors present the design of the shipping simulation SEL and its integration in the MSP Challenge Simulation Platform. This platform is designed to give policymakers and planners insight into the complexity of Maritime Spatial Planning (MSP) and can be used for interactive planning support. It uses advanced game technology to link real geo- and marine data with simulations for ecology, energy and shipping. The shipping sector is an important economic sector with influential stakeholders. SEL calculates the (future) impact of MSP decisions on shipping routes. This is dynamically shown in key performance indicators (e.g. route efficiencies) and visualised in heat maps of ship traffic. SEL uses a heuristic-based graph-searching algorithm to find paths from one port to another during each simulated month. The performance of SEL was tested for three sea basins: the firth of Clyde, Scotland (smallest), North Sea (with limited data) and Baltic Sea regions (largest, with most complete data). The behaviour of the model is stable and valid. SEL takes between 4 and 17 seconds to generate the desired monthly output. Experiences in 20 sessions with 302 planners, stakeholders and students indicate that SEL is a valuable addition to MSP Challenge, and thereby to MSP.
Abstract
The authors present the design of the shipping simulation SEL and its integration in the MSP Challenge Simulation Platform. This platform is designed to give policymakers [...]
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Applying OSiRIS NMAL to Network Slices on SLATE
J. Musser, E. Kissel, M. Swany, J. Breen, J. Stidd, S. McKee, B. Meekhof

Collection of open conferences in research transport (2019). Vol. 2019, 66

Abstract
We will present techniques developed in collaboration with the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) and SLATE (NSF Award #1724821) for orchestrating software defined network slices with a goal of building reproducible and reliable computer networks for large data collaborations. With this project we have explored methods of utilizing passive and active measurements to build a carefully curated model of the network. We will show that by then using such a model, we can dynamically and programmatically alter network and host configuration to effectively respond to changing network conditions. As part of our presentation, we will show how SLATE, operating over a slice of the Internet2 network, provides a container focused platform for running a Network Management Abstraction Layer (NMAL), allowing us to control applications in a reliable and reproducible way. This presentation will demonstrate how NMAL tracks live network topological and performance statistics on an Internet2 slice with SLATE-enabled hosts to enact traffic engineering and container placement decisions in order to optimize network behavior based on user defined profiles. We will conclude by discussing the future of this work and our plans for using it to support science activities in production. Document type: Article
Abstract
We will present techniques developed in collaboration with the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) and SLATE (NSF Award #1724821) for orchestrating software [...]
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Automatic Labeled LiDAR Data Generation based on Precise Human Model
M. Tanaka, M. Okutomi, W. Kim, Y. Sasaki

Collection of open conferences in research transport (2019). Vol. 2019, 65

Abstract
Following improvements in deep neural networks, state-of-the-art networks have been proposed for human recognition using point clouds captured by LiDAR. However, the performance of these networks strongly depends on the training data. An issue with collecting training data is labeling. Labeling by humans is necessary to obtain the ground truth label; however, labeling requires huge costs. Therefore, we propose an automatic labeled data generation pipeline, for which we can change any parameters or data generation environments. Our approach uses a human model named Dhaiba and a background of Miraikan and consequently generated realistic artificial data. We present 500k+ data generated by the proposed pipeline. This paper also describes the specification of the pipeline and data details with evaluations of various approaches. Comment: Accepted at ICRA2019
Abstract
Following improvements in deep neural networks, state-of-the-art networks have been proposed for human recognition using point clouds captured by LiDAR. However, the performance [...]
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Research on Traffic Congestion Resolution Mechanism based on Genetic Algorithm and Multi-Agent
S. Cheng, Z. Zhang, J. Ye

Collection of open conferences in research transport (2019). Vol. 2019, 64
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Development and challenge of paste technology in China
A. Wu, Y. Yang, L. Zhang, H. Cheng

Collection of open conferences in research transport (2019). Vol. 2019, 63

Abstract
paste technology can effectively ensure safe mining conditions and realize green mining, it has been popularized and widely applied in China in recent years. Meanwhile, with the development of intelligent control, precise preparation and personalized filling, studies on paste technology in China have also been deepened. In this paper, the basic concepts and characteristics of paste technology were introduced, and the development of paste technology in China was analyzed statistically. It systematically analyzed the latest research progress in thickening dewatering of unclassified tailings, pipeline transportation of structure flow, multi-field influence in stopes, development of new materials and construction of paste engineering laboratory. The practical effects of paste technology in underground backfill and surface deposition were also introduced. In the future, paste technology will achieve great breakthroughs by digitization and intelligence and realize adaptive control of concentration, precision preparation of paste, personalized filling of stopes and 3D and modular design and assembly of system, leading mining industry in China to the path of green development.
Abstract
paste technology can effectively ensure safe mining conditions and realize green mining, it has been popularized and widely applied in China in recent years. Meanwhile, with [...]
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Object detection, lane detection, and free space detection
G. Dubbelman, A. Das, N. Kemsaram

Collection of open conferences in research transport (2019). Vol. 2019, 62

Abstract
In this paper, we present a deep neural network based real-time integrated framework to detect objects, lane markings, and drivable space using a monocular camera for advanced driver assistance systems. The object detection framework detects and tracks objects on the road such as cars, trucks, pedestrians, bicycles, motorcycles, and traffic signs. The lane detection framework identifies the different lane markings on the road and also distinguishes between the ego lane and adjacent lane boundaries. The free space detection framework estimates the drivable space in front of the vehicle. In our integrated framework, we propose a pipeline combining the three deep neural networks into a single framework, for object detection, lane detection, and free space detection simultaneously. The integrated framework is implemented in C++ and runs real-time on the Nvidia's Drive PX 2 platform.
Abstract
In this paper, we present a deep neural network based real-time integrated framework to detect objects, lane markings, and drivable space using a monocular camera for advanced [...]
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Trajectory Phase–Plane Method – Based Analysis of Stability and Performance of a Fuzzy Logic Controller for an Anti–Lock Braking System
A. Andrei, R. Vincenzo, V. Valery, A. Klaus

Collection of open conferences in research transport (2019). Vol. 2019, 61

Abstract
The trajectory phase–plane method provides an increased significance to the analysis of stability and performance of the controllers for complex nonlinear plants. The aim of this study is the stability and performance analysis of a fuzzy logic controller for anti–lock braking system applying the trajectory phase–plane technique. The controller’s main task is to hold optimal braking performance by recognizing road surface. The stability and performance of the anti–lock braking system controller are examined with respect to the conventional friction brake and electric motors separately. The applied methodology allows for visual assessment of the stability and performance of studied nonlinear systems. The work refers to hardware–in–the–loop simulations conducted at the Technische Universität Ilmenau. The results demonstrate that the fuzzy logic controller is stable independently of the employed actuator. Moreover, the electric actuators allow for faster convergence and more accurate tracking of the optimal wheel slip.
Abstract
The trajectory phase–plane method provides an increased significance to the analysis of stability and performance of the controllers for complex nonlinear plants. The aim [...]
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TransAID
J. Schindler

Collection of open conferences in research transport (2019). Vol. 2019, 60
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Possibilities of using bus rapid transit in cities with dense construction area
Y. Royko, R. Bura, R. Rogalskyy

Collection of open conferences in research transport (2019). Vol. 2019, 59

Abstract
Bus rapid transit (BRT) is one of the most popular mass passenger transportation systems as it is cost-effective, comfortable and rapid during its use, hence it is widespread in developing countries. In the paper, the classification of urban public transport modes is highlighted and the main components of BRT system are given. Also, types of running ways on highways and other urban streets are classified and also measures aimed at giving the priority to public transport in mixed traffic are given.
Abstract
Bus rapid transit (BRT) is one of the most popular mass passenger transportation systems as it is cost-effective, comfortable and rapid during its use, hence it is widespread [...]
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Virtual Traffic Lights: System Design and Implementation
I. Ozgunes, A. Pomini, L. Basseto, A. Ishikawa, O. Tonguz, F. Schmutz, S. Hassen, K. Gerard, R. Zhang

Collection of open conferences in research transport (2019). Vol. 2019, 58

Abstract
Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual Traffic Lights (VTL) has been proposed for mitigating traffic congestion. VTL is an infrastructure free traffic control scheme that leverages the presence of Vehicle-to-Vehicle (V2V) communications. Such infrastructure free scheme has several benefits, such as alleviating traffic congestion; reducing the large cost of traffic lights and traffic control systems; reducing carbon emission, etc. This paper reports a DSRC-based prototype design effort on VTL using Dedicated Short Range Communications (DSRC) technology. The experiments performed show the feasibility of implementing VTL with DSRC technology. Preliminary results of the field tests conducted in Pittsburgh with vehicles using VTL equipment indicate that VTL is capable of coordinating traffic at intersections and reducing the commute time of people. Comment: 5 pages, 7 figures Accepted by Vehicular Technology Conference 2018 (2018)
Abstract
Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as [...]
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A novel application of models of species abundance to better understand OpenStreetMap community structure and interactions
P. Mooney

Collection of open conferences in research transport (2019). Vol. 2019, 57

Abstract
Mooney (2019). A novel application of models of species to better understand OpenStreetMap Community structure and interactions In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 5-6. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3386559
Abstract
Mooney (2019). A novel application of models of species to better understand OpenStreetMap Community structure and interactions In: Minghini, M., Grinberger, A.Y., Juhász, [...]
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Energy management for electric vehicles in smart cities: a deep learning approach
M. Marot, M. Laroui, H. Moungla, H. Afifi, A. Dridi, M. Cherif

Collection of open conferences in research transport (2019). Vol. 2019, 56

Abstract
International audience; We propose a solution for Electric Vehicle (EV) energy management in smart cities, where a deep learning approach is used to enhance the energy consumption of electric vehicles by trajectory and delay predictions. Two Recurrent Neural Networks are adapted and trained on 60 days of urban traffic. The trained networks show precise prediction of trajec-tory and delay, even for long prediction intervals. An algorithm is designed and applied on well known energy models for traction and air conditioning. We show how it can prevent from a battery exhaustion. Experimental results combining both RNN and energy models demonstrate the efficiency of the proposed solution in terms of route trajectory and delay prediction, enhancing the energy managemen
Abstract
International audience; We propose a solution for Electric Vehicle (EV) energy management in smart cities, where a deep learning approach is used to enhance the energy consumption [...]
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Report on a Hackathon for Car Navigation Using Traffic Risk Data
K. Zettsu, S. Ito

Collection of open conferences in research transport (2019). Vol. 2019, 55

Abstract
Car drivers select their routes based on the information obtained about accidents and traffic congestion along the route. In recent years, nowcasting and forecasting of various traffic risk events is being performed by using diverse sensor data. However, there is no clarity as yet on what and how to communicate to the driver in case there are traffic risks on the route. In this paper, we have developed an environment that enables non UI experts to quickly create car navigation prototypes by using traffic risk data. This paper includes our report on a hackathon that we held using this environment. The hackathon theme was "Develop a new car navigation system equipped with a mechanism that makes the driver aware of traffic risks and helps them determine the most appropriate driving routes." Twenty three researchers and professionals from the field of traffic engineering participated. Our results have brought certain common problems to the awareness of the experts. The information obtained from this report will be very beneficial for our community to determine the direction of collaboration.
Abstract
Car drivers select their routes based on the information obtained about accidents and traffic congestion along the route. In recent years, nowcasting and forecasting of various [...]
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