Scipedia: Documents published in 2017

External costs estimation in a cost-benefit analysis: The new Formia-Gaeta tourist railway line in Italy

Scipedia content — Mon, 08 Feb 2021 09:43:18 +0100

In 2016 a new law for public contract was approved in Italy also aimed at improving the national and local sustainable transport planning. The Italian government has also adopted new 'Guidelines for assessment the Investment Projects' derived from the European Commission indications about the external costs of transport estimation in the Cost-Benefit Analysis. Starting from these considerations, the aim of this paper was to propose a new methodology, in compliance with the Italian guidelines, for the estimation of the external costs of transport in a Cost-Benefit Analysis. The application case study was a new tourist railway line in Lazio Region. The external costs estimated were the variations in term of: climate change, air pollution, noises, congestion and road accident. Estimations results allow to conclude that there is a social convenience of this new rail infrastructure because: i) a positive Net Present Value equal to about 27 Mâ¬ was estimated; ii) an Internal Rate of Return much greater than the discount rate (9% vs. 3%) was observed; iii) a benefit/cost ratio equal to 2 and a PayBack Period of 15 years was quantified. The overall amount (in monetary value) of external costs saved is about 360 thousand Euros/year (2016 prices) with a cumulative value, for all the life-period considered (30 years), equal to 11 million of Euros.

Hierarchical Decomposition Approach for Detailed Scheduling of Pipeline Systems with Branches

Scipedia content — Mon, 08 Feb 2021 09:42:26 +0100

Scheduling multiproduct pipelines is a complex managerial task with a remarkable impact on the total revenues of the pipeline industry. It consists of sequencing, sizing and timing of injections and removals, to meet product demands on time at minimum cost. Generating the detailed scheduling of pipeline networks can be very challenging, requiring efficient optimization tools to find good feasible solutions. This paper develops a hierarchical decomposition approach for tree-like pipeline systems with two-level branching. Decisions related to the sequence of product injections and the destination for each batch, are made at the higher planning layer, while the lower layer then finds the sequence and timing of product deliveries. Each layer is tackled by a mixed-integer linear programming (MILP) formulation, which neither discretizes the time horizon nor divides a pipeline segment into packs of equal size. Solutions to three case studies present significant reductions in both the operating cost and the computational burden.

Stakeholder impact on the software architecture of intelligent transport systems implementations

Scipedia content — Mon, 08 Feb 2021 09:40:40 +0100

Modern vehicles are equipped with a lot of hard-and software systems that all generate in-vehicle data. Application development could benefit from a generic data acquisition layer to create a healthy, transparent and ethical data sharing environment. This paper investigates which policies are necessary in order to create this environment to stimulate development of applications that require access to in-vehicle data.

The effect of see-through truck on driver monitoring patterns and responses to critical events in truck platooning

Scipedia content — Mon, 08 Feb 2021 09:40:27 +0100

utomated platooning of trucks has its beneficial effects on energy saving and traffic flow efficiency. The vehicles in a platoon, however, need to maintain an extremely short headway to achieve these goals, which will result in a heavily blocked front view for the driver in a following truck. Monitoring surrounding traffic environment and foreseeing upcoming hazardous situations becomes a difficult, yet safety-critical task. This exploratory study aims to investigate whether providing platoon drivers with additional visual information of the traffic environment can influence their monitoring pattern and increase awareness of the upcoming situation. 22 professional truck drivers participated in the driving simulator experiment, either following a see-through lead truck (i.e., with projection of forward scene attached to the rear of the lead truck), or a normal lead truck until the automation system failed unexpectedly in a critical situation. Results showed that when provided with front view projection, the participants spent 10% more time monitoring the road, and responded less severely to a critical situation, suggesting a positive effect of the “see-through” technology.

Numerical Modelling of Interference from AC Power Lines on Buried Metallic Pipelines in Presence of Mitigation Wires

Scipedia content — Mon, 08 Feb 2021 09:40:01 +0100

This paper presents a numerical approach based on the finite element method for the estimation of AC interference on buried metallic pipelines sharing the same right-of-way of power transmission lines in presence of mitigation wires. The proposed approach relies on a hybrid technique in order to reduce the mesh size and, in turn, the computational time. The feasibility of the method is demonstrated with application to a standard interference configuration. Some tests were performed in order to assess how the position and material of the mitigation wires affect the induced current on a buried metallic pipeline.

Driving into the memory wall

Scipedia content — Mon, 08 Feb 2021 09:39:34 +0100

utonomous driving is disrupting conventional automotive development. Underlying reasons include control unit consolidation, the use of components originally developed for the consumer market, and the large amount of data that must be processed. For instance, Audi's zFAS or NVIDIA's Xavier platform integrate GPUs, custom accelerators, and CPUs within a single domain controller to perform sensor fusion, processing, and decision making. The communication between these heterogeneous components and the algorithms for Advanced Driver Assistance Systems and Autonomous Driving require low latency and huge memory bandwidth, bringing the Memory Wall from high-performance computing in data centers directly to our cars. In this paper we discuss these and other requirements in using DRAM for near-term autonomous driving architectures.

Evaluation of safety indicators for truck platooning

Scipedia content — Mon, 08 Feb 2021 09:39:19 +0100

This paper addresses safety indicators for truck platooning at short inter-vehicle distances (with a time gap of 0.5 s). The aim of a safety indicator is to determine the correct moment for initiating a Collision Avoidance brake action to prevent a collision with the preceding truck in threatening situations. Three safety indicators are selected for an evaluation: the intended acceleration of the preceding truck, which is shared via Vehicle-to-Vehicle (V2V) communication, the Brake Threat Number (BTN — based on simple vehicle models and an emergency brake assumption of the lead), and the Time-To-Collision (TTC — based on a constant velocity assumption). The latter two do not rely on V2V communication, but are obtained via on-board signals. Requirements for the amount of false negatives (missing a threatening situation) and the false positives (identifying a safe situation as threatening) are derived from a functional safety perspective. To find thresholds for the safety indicators that minimize the false negative rate, emergency brake tests are used. To evaluate the number of false positives, a set of data of two trucks driving in a platoon at 0.5 s at mixed-traffic highways in Belgium and the Netherlands, collected during 8 hours of automated driving in a platoon, is used. The results indicate that the communicated intended acceleration of the preceding truck might be able to distinguish safe and threatening situations in a vehicle platoon. Furthermore, for situations without V2V, both the BTN and the TTC are not capable to distinguish between threatening and safe situations. The amount of false positives found in the safe driving data-set does not fulfill the requirements derived from functional safety perspective.

Multi-agent system for managing energy storage using electric vehicles

Scipedia content — Sun, 07 Feb 2021 13:48:42 +0100

The thesis addresses the challenges related to management of energy storage with electric vehicles (EVs). Charging of EV batteries is a time-consuming process with the current state of technology and therefore, the process of charging is often coupled with the process of parking. This thesis builds on that assumption and proposes a solution how to design a parking lot with EV charging functionality so that the parking lot operator's profit is maximized while, simultaneously, the need of EV owners for parking and energy is fulfilled. Therefore, this thesis focuses on EV energy storage management through answering the questions when, where, at what price, and how long an EV should park in an EV-enabled parking spot. The original scientific contribution has been achieved as follows: - An energy storage model of electric vehicles realized as a multi-agent system consisting of electric vehicle agents, parking lot agent and electricity market agent. - Algorithms (policies) for managing energy storage based on contextual and technical factors describing electric vehicles and a parking lot, and economic inputs from electricity market. - Evaluation and techno-economic analysis of proposed algorithms for managing energy storage through an agent-based simulation of electric vehicle enabled parking lot. Doktorski se rad bavi izazovima vezanim uz upravljanje skladištenja energije s pomoću električnih vozila (EV-a). Punjenje baterija EV-a trenutno je dugotrajan proces zbog čega se navedeni proces često uparuje s procesom parkiranja. Disertacija koristi navedenu pretpostavku te predlaže rješenje za dizajn parkirališta s uslugom punjenja EV-a na način da je profit operatora parkirališta maksimiziran te da su zadovoljene potrebe vlasnika EV-a vezane uz parkiranje i punjenje. Zbog toga se disertacija fokusira na upravljanje skladištenjem energije s pomoću električnih vozila odgovaranjem na pitanja kada, gdje, po kojoj cijeni i koliko dugo EV-evi moraju parkirati na parkirno mjesto s punjačem. Ostvaren je sljedeći izvorni znanstveni doprinos: -Model skladištenja energije s pomoću električnih vozila, ostvaren kao višeagentski sustav koji se sastoji od agenata električnih vozila, agenta parkirališta i agenta tržišta električne energije. -lgoritmi (pravila) za upravljanje skladištenjem energije zasnovani na kontekstualnim i tehničkim obilježjima električnih vozila i parkirališta te relevantnim ekonomskim podacima s tržišta električne energije. -Evaluacija i tehno-ekonomska analiza predloženih algoritama za upravljanje skladištenjem energije kroz agentsku simulaciju parkirališta s podrškom za električna vozila.

Demand Response and Energy Portfolio Optimization for Smart Grid using Machine Learning and Cooperative Game Theory

Scipedia content — Sun, 07 Feb 2021 13:47:51 +0100

Key performance indicators for assessing the impacts of automation in road transportation: Results of the Trilateral key performance indicator survey

Scipedia content — Sun, 07 Feb 2021 13:38:30 +0100

Research and Application of Public Traffic Intelligent Dispatching Based on Dynamic Programming Algorithm

Scipedia content — Wed, 03 Feb 2021 21:55:21 +0100

Enabling Driver Feet Gestures Using Capacitive Proximity Sensing

Scipedia content — Wed, 03 Feb 2021 21:53:30 +0100

Due to driver assistance systems and the trend of industry towards automated driving, the hands and feet of the driver in a vehicle require less intervention, becoming even idle. Recent gesture recognition focuses on hand interaction. This paper provides feet gesture interaction. Many gesture recognition systems rely on computing intensive video systems, causing privacy concerns. Furthermore, these systems require a line of sight and therefore a visible interior design integration. Our system proves that invisibly integrated capacitive proximity sensors can do this as well. They do not cause privacy issues and can be integrated under non-conductive materials. Therefore, there is no impact on the design of the visible interior. Our proposed solution distinguishes between four feet gestures. There is no limitation to feet movement. Further, we prove the functionality of the system in an evaluation with six participants, using a prototypical mock-up of a vehicle legroom. %This project contributes to the basis of driver feet gesture recognition pointing to further applications and more comprehensive investigations.

Fault detection and isolation in flat navigation canals

Scipedia content — Wed, 03 Feb 2021 21:53:03 +0100

Trabajo presentado a la 4th International Conference on Control, Decision and Information Technologies (CoDIT), celebrada en Barcelona (España) del 5 al 7 de abril de 2017.

Inland navigation networks are composed of several artificial canals that are characterized by no slope. These canals are particularly subject to resonance phenomena, which can create waves such that the navigation condition might not be guaranteed. It is therefore required to ensure dealing with freefault measured data and actuators. In this work, a fault detection and isolation method based on the Integrator Delay Zero model (IDZ) is designed for flat navigation canals. The proposed method is dedicated to the detection and isolation of sensor and actuator faults. Finally, it is tested by considering the Cuinchy-Fontinettes canal located in the north of France.

This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (MINECOP) and FEDER through the project HARCRICS (ref. DPI2014-58104-R) and through the grant IJCI-2014-2081.

Peer Reviewed

Document type: Conference object

Sustainable Decision-Making using the COMET Method: An Empirical Study of the Ammonium Nitrate Transport Management

Scipedia content — Wed, 03 Feb 2021 21:40:27 +0100

This paper investigates the problem of the sustainable ammonium nitrate transport. The significance of this problem is increasing, considered the occurrence of the worldwide agricultural production boost. The existing international regulations for the transport of the dangerous chemical substances are not sufficient to obtain a satisfactory solution for the sustainable transport. The main reason for that is the fact that the safety criteria can easily become dominated by the economic factors. In this paper, the authors use the COMET method to identify a decision making model for the selection of the best scenario of sustainable transport. The COMET method is a new multi-criteria decision-making technique that is free of the rank reversal phenomenon. The identified model provides information about the global and local significance level of each of the criteria. The proposed approach can be easily expanded by using a greater number of criteria, depending on the particular problem analyzed. The proposed methodology is an efficient and highly accurate solution to make decisions based on experts' knowledge.

Impact analysis of freight vehicle access restriction (A case study of Jakarta Intra Urban Toll way)

Scipedia content — Wed, 03 Feb 2021 21:27:41 +0100

Since the access restriction policy on freight vehicles was implemented in some parts of Jakarta Intra-Urban Tollway (JIUT) in 2011, i.e. section Cawang – Tomang – Pluit, several sections had an improved performance. However, there were sections that showed the opposite effect. The purpose of this research was to analyze the impact of the policy on JIUT as a whole by using the parameters based on sustainable transportation indicators. The study area was divided into the statutory segment (Cawang – Tomang – Pluit) and the affected segment (Cawang – Tanjung Priok – Pluit). The assessment results of five parameters including travel time, fuel consumption, fatality rate, CO2 emissions, and noise level indicated that the implementation of the policy provided an advantage to the traffic smoothness priority at the statutory segment, but it did not support the sustainable urban transportation priority of the entire JIUT system. The proposed solution to maintain the sustainable condition of urban transportation is...

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

Scipedia content — Wed, 03 Feb 2021 21:26:51 +0100

A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing

Scipedia content — Wed, 03 Feb 2021 21:24:22 +0100

This paper proposes a deep neural network structure that exploits edge information in addressing representative low-level vision tasks such as layer separation and image filtering. Unlike most other deep learning strategies applied in this context, our approach tackles these challenging problems by estimating edges and reconstructing images using only cascaded convolutional layers arranged such that no handcrafted or application-specific image-processing components are required. We apply the resulting transferrable pipeline to two different problem domains that are both sensitive to edges, namely, single image reflection removal and image smoothing. For the former, using a mild reflection smoothness assumption and a novel synthetic data generation method that acts as a type of weak supervision, our network is able to solve much more difficult reflection cases that cannot be handled by previous methods. For the latter, we also exceed the state-of-the-art quantitative and qualitative results by wide margins. In all cases, the proposed framework is simple, fast, and easy to transfer across disparate domains.

Comment: Appeared at ICCV'17 (International Conference on Computer Vision)

Comparing MapReduce and Pipeline implementations for Counting Triangles

Scipedia content — Wed, 03 Feb 2021 21:24:08 +0100

common method to define a parallel solution for a computational problem consists in finding a way to use the Divide and Conquer paradigm in order to have processors acting on its own data and scheduled in a parallel fashion. MapReduce is a programming model that follows this paradigm, and allows for the definition of efficient solutions by both decomposing a problem into steps on subsets of the input data and combining the results of each step to produce final results. Albeit used for the implementation of a wide variety of computational problems, MapReduce performance can be negatively affected whenever the replication factor grows or the size of the input is larger than the resources available at each processor. In this paper we show an alternative approach to implement the Divide and Conquer paradigm, named dynamic pipeline. The main features of dynamic pipelines are illustrated on a parallel implementation of the well-known problem of counting triangles in a graph. This problem is especially interesting either when the input graph does not fit in memory or is dynamically generated. To evaluate the properties of pipeline, a dynamic pipeline of processes and an ad-hoc version of MapReduce are implemented in the language Go, exploiting its ability to deal with channels and spawned processes. An empirical evaluation is conducted on graphs of different topologies, sizes, and densities. Observed results suggest that dynamic pipelines allows for an efficient implementation of the problem of counting triangles in a graph, particularly, in dense and large graphs, drastically reducing the execution time with respect to the MapReduce implementation.

Comment: In Proceedings PROLE 2016, arXiv:1701.03069

Document type: Article

Evolutionary computation at work for the optimization of link state routing protocols

Scipedia content — Wed, 03 Feb 2021 21:20:24 +0100

This work explores the optimization of a real-valued parameter, assigned to each network node running the Distributed Exponentially-weighted Flow SpliTting (DEFT) routing protocol, in order to address changes on traffic conditions. This new proposal avoids the need to alter link weights and forwarding paths, by adjusting traffic splitting. In this context, we explore the use of Evolutionary Algorithms both in single and multi-objective optimization problems, to obtain solutions that minimize network's congestion. We thank the Portuguese FCT under the scope of the strategic funding of UID/BIO/04469/2013 unitand COMPETE 2020(POCI-01-0145-FEDER-006684) and BioTecNorte (NORTE-010145-FEDER-000004) funded by European Regional Development Fund (Norte2020-ProgramaOperacionalRegionaldoNorte). info:eu-repo/semantics/publishedVersion

Detection of non-recurrent road traffic events based on clustering indicators

Scipedia content — Wed, 03 Feb 2021 21:19:49 +0100

International audience; Based on a clustering indicator, an alteration of the classical road traffic indicators is proposed for incident detection. The resulting filter method reduces the inaccuracies of comparable detection method and enables to better separate usual traffic patterns from non-recurrent situations. Three alternative detection approaches are considered as baseline comparison for performance estimation.

A real-time autonomous highway accident detection model based on big data processing and computational intelligence

Scipedia content — Wed, 03 Feb 2021 21:18:36 +0100

Due to increasing urban population and growing number of motor vehicles, traffic congestion is becoming a major problem of the 21st century. One of the main reasons behind traffic congestion is accidents which can not only result in casualties and losses for the participants, but also in wasted and lost time for the others that are stuck behind the wheels. Early detection of an accident can save lives, provides quicker road openings, hence decreases wasted time and resources, and increases efficiency. In this study, we propose a preliminary real-time autonomous accident-detection system based on computational intelligence techniques. Istanbul City traffic-flow data for the year 2015 from various sensor locations are populated using big data processing methodologies. The extracted features are then fed into a nearest neighbor model, a regression tree, and a feed-forward neural network model. For the output, the possibility of an occurrence of an accident is predicted. The results indicate that even though the number of false alarms dominates the real accident cases, the system can still provide useful information that can be used for status verification and early reaction to possible accidents.

The effect of wind turbines alongside motorways on drivers’ behaviour

Scipedia content — Wed, 03 Feb 2021 21:17:59 +0100

This paper presents the results of a first study aimed at investigating whether the presence of wind turbines in close proximity to motorways leads to behavioural adaptations among passing drivers. Empirical data from loop detectors and temporary video cameras were analysed in a study employing a before-and-after design at a site near Rotterdam, The Netherlands. Analyses of driving speed and standard deviation of speed (corrected for trend effects through the use of control sites) were performed as well as analyses of the lateral position and standard deviation of the lateral position and an observation of serious traffic conflicts. The results showed that constructing wind turbines alongside a motorway led to some clearly observable effects on drivers’ behaviour. The analyses of the speed data showed that the mean speed was lowered by 2.24km/h (corrected for trend effects) after the construction of the wind turbines while the standard deviation of the speed significantly increased. After the construction of the wind turbines, drivers took a lateral position somewhat more to the left-hand side in their driving lane. There was an indication close to the 0.05 significance level (p=0.057) that the standard deviation of the lateral position slightly increased when the rotor blades were in transversal position. In the before period as well as in the after period, no serious traffic conflicts were registered. The increase in standard deviation of speed and in lateral position are two factors that intrinsically can have an unfavourable effect on road safety. However, the observed order of magnitude of the change was shown to be quite limited. Earlier research suggests that negative effects on road safety are only expected for changes substantially greater than the ones that were observed in this study. On the other hand, there was a significant reduction in driving speed, which might have a favourable effect on the expected number and severity of crashes, although it could also be a compensatory mechanism that indirectly indicates a reduced driving performance. From these findings, it can be concluded that, based on the observed variables, no substantial negative effects for road safety were found in the present study. The authors recommend continuous monitoring and further research on the topic.

Learning Air Traffic Controller Workload from Past Sector Operations

Scipedia content — Wed, 03 Feb 2021 21:16:27 +0100

International audience; In this paper, we compare several machine learning methods on the problem of learning a model of the air traffic controller workload from historical data. This data is a collection of workload mesurements extracted from past sector operations and of ATC complexity measurements computed from radar records and airspace data (sector geometry). We assume that the workload is low when a given sector is collapsed with other sectors into a larger sector, normal when it is operated as is, and high when it is split into smaller sectors assigned to several working positions. This learning problem is modeled as a classification problem where the target variable is a workload category (low, normal, high) and the explanatory variables are the air traffic control (ATC) complexity metrics. Several classifiers are compared on this problem: linear dis-criminant analysis, quadratic discriminant analysis, naive Bayes classifiers, neural networks, and gradient boosted trees. The performance of these models is assessed on a separate test set. The best methods show a rate of correct predictions around 82%.

Information Modeling for Thermal Fatigue Evaluation of Power Plant Pipelines

Scipedia content — Wed, 03 Feb 2021 21:11:53 +0100

Bayesian Test Design for Reliability Assessments of Safety-Relevant Environment Sensors Considering Dependent Failures

Scipedia content — Wed, 03 Feb 2021 21:04:03 +0100

Machine vision based on automotive environment sensors is the enabling technology for advanced driver assistance systems and automated driving. Due to its important role, the reliability of environment sensing is highly safety relevant and has thus to be assessed and demonstrated during the development of the system. The main challenges associated with this task are low target error rates and the stochastic influence of different uncertain environmental conditions on the sensor performance. As a basis for the reliability assessment of environment sensors we introduce comprehensive performance metrics that allow a formal description of the uncertainties in a digital environmental model. Due to the influence of environmental conditions on the sensor performance, these metrics however are not constant but are random variables themselves. This leads to a hierarchical uncertainty structure including higher order uncertainties. To quantify the influence of the environmental conditions on the sensor reliability, we use a Bayesian hierarchical regression model. The utility of this method is demonstrated with a case study in which the influence of temperature on sensor reliability is examined. The results show that the proposed methodology is capable of identifying and quantifying the influence of the temperature on sensor performance. The introduced metrics and the proposed methodology are an important step towards a formalized reliability assessment of automotive environment sensing. In order to predict if the sensor reliability complies with the target error rates, the presented methodology has to be adapted and extended with additional stochastic methods.

One step at a time: Optimizing SDN upgrades in ISP networks

Scipedia content — Wed, 03 Feb 2021 21:01:42 +0100

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Nowadays, there is a fast-paced shift from legacy telecommunication systems to novel Software Defined Network (SDN) architectures that can support on-the-fly network reconfiguration, therefore, empowering advanced traffic engineering mechanisms. Despite this momentum, migration to SDN cannot be realized at once especially in high-end cost networks of Internet Service Providers (ISPs). It is expected that ISPs will gradually upgrade their networks to SDN over a period that spans several years. In this paper, we study the SDN upgrading problem in an ISP network: which nodes to upgrade and when. We consider a general model that captures different migration costs and network topologies, and two plausible ISP objectives; first, the maximization of the traffic that traverses at least one SDN node, and second, the maximization of the number of dynamically selectable routing paths enabled by SDN nodes. We leverage the theory of submodular and supermodular functions to devise algorithms with provable approximation ratios for each objective. Using real-world network topologies and traffic matrices, we evaluate the performance of our algorithms and show up to 54% gains over state-of-the-art methods. Moreover, we describe the interplay between the two objectives; maximizing one may cause a factor of 2 loss to the other. EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe

Openstreetmap A Servizio Delle Emergenze

Scipedia content — Wed, 03 Feb 2021 21:01:14 +0100

These slides (in Italian) were presented during the FOSS4G-IT 2017 conference, held in Genova (Italy) on February 9-10, 2017 (http://www.dicca.unige.it/geomatica/foss4git_2017/index.html). The presentation is about the exploitation of OpenStreetMap (OSM) database in the emergency stage and focuses on the activities of the Italian OSM community after the earthquakes in Central Italy happened in late 2016.

The Research of Optimal Length of Left Turn with U-turn at Intersection Based on Statistical and Simulation Analysis

Scipedia content — Wed, 03 Feb 2021 20:59:16 +0100

Identifying barriers in shared mobility implementation, a review

Scipedia content — Wed, 03 Feb 2021 20:56:32 +0100

Urban mobility options have substantially increased in recent years, enabled by the widespread availability of smart device software Apps, geo-positioning technology, and the ease of electronic financial transactions. These options are likely to be supplemented soon by the rapidly advancing development of autonomous vehicles. Commercial sharing services,such as share cars and share bicycles, are expecting to complement fixed route public transit systems to support the first/last mile challenge of public transit services [a part of Mobility asa Service (MaaS)], as well as stimulate additional demand for short distance mobility. This paper reviews the development of commercial bike and car sharing schemes, then examines the technologies and policies that support MaaS. This research draws upon the experiences learnt and indicates the potential difficulties encountered in the successful planning of shared mobility services. The results provide an in-depth discussion of the characteristics and needs of shared mobility services and investigates the barriers of applying the Internet of Things (IoT), cybersecurity and blockchain in first/last mile mobility challenge. The findings will assist the community, business providers and government policymakers who are keen to promote shared mobility as a pathway towards more efficient, environmentally sustainable and socially responsive mobility solutions.

Developments in Cooperative Intelligent Vehicle-Highway Systems and Human Factors Implications

Scipedia content — Wed, 03 Feb 2021 20:52:31 +0100

Cooperative vehicle-highway systems offer the potential to enhance the effectiveness of active vehicle safety systems which have entered the marketplace for light vehicles and heavy commercial vehicles. Cooperative intelligent vehicle-highway systems (IVHS) offer an improved level of overall functionality. These systems are "cooperative" in that the vehicles can receive information from the roadway and respond appropriately, and vehicles can detect and report hazards to the roadway, for dissemination to other travelers. The systems are "intelligent" in that the ultimate response is determined by algorithms which weigh multiple parameters. This paper describes the results of a study to collect information on the various forms of cooperative IVHS worldwide, and assess research and development activities, deployment issues, standards development, and government policies. An extensive set of parameters which may pass between the vehicle and its external environment are listed. Potential human factors implications are identified, resulting from the emergence of these driver assistance systems into the marketplace.

Osm Seen From A Gis Researcher: Experiences & Perspectives

Scipedia content — Wed, 03 Feb 2021 20:49:05 +0100

These slides were presented at State of the Map 2017 conference in Aizu-Wakamatsu, Japan (http://2017.stateofthemap.org). They aim to provide an overview on some current research trends on OpenStreetMap (OSM), focusing in particular on three research works I have carried out over the last few years: 1) an automated procedure for quality assessment of OSM road networks; 2) an analysis of OSM tagging patterns; and 3) the use of OSM to generate Land Use/Land Cover maps.

Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

Scipedia content — Wed, 03 Feb 2021 20:48:53 +0100

Electric vehicles (EVs) are becoming a key feature of smart grids. EVs will be embedded in the smart grids as a mobile load-storage with probabilistic behavior. In order to manage EVs as flexible loads, charging stations (CSs) have essential roles. In this paper, a new method for optimal sitting and sizing of solar CSs using energy storage (ES) options is presented. Also, behavior of EVs in the presence of other loads, electricity price and solar power generation uncertainties are considered. The proposed optimization model maximizes the distribution company (DisCo) benefit by appropriate use of CSs, maximizes the benefit of CSs owners and minimizes the power loss, load demand and voltage sags during peak times considering different technical constraints. The optimization variables are the location and capacity of solar units and energy storage systems. In this paper, charge-discharge process of EVs are considered based on time-of-use (TOU) demand response programs (DRPs). In order to solve the optimization problem considering uncertainty of load growth, electricity price, initial state of charge of batteries and solar power generation, genetic algorithm method using Monte-Carlo simulation is used. The simulation results show that the proposed method has advantages for DisCo and owners of CSs.

Simulating impacts of regulatory policies on urban freight: application to the catering setting

Scipedia content — Wed, 03 Feb 2021 20:44:26 +0100

International audience; Regulatory policies aim at reducing the negative effects of urban freight transportation, especially those related to traffic, emissions and noise. Nonetheless, stakeholders in city logistics often have divergent objectives, which lead to difficulties upon defining the best possible choices regarding regulation. This paper presents a multi-agent and discrete-event based simulation of urban deliveries that aims at evaluating the impacts of regulatory policies. Restrictions regarding vehicle weights and time windows are considered in order to measure the impacts on deliveries based on total distances, number of vehicles, loading rates and air pollutant emissions. The simulation framework is applied to the delivery services for restaurants, in which 4 scenarios of regulation are evaluated in the city of Paris. One originality of the proposed approach is to use real data for the instantiation of agents and the GIS in the simulation.

Towards a sustainable hydrogen economy: Optimisation-based framework for hydrogen infrastructure development

Scipedia content — Wed, 03 Feb 2021 20:42:48 +0100

This work studies the development of a sustainable hydrogen infrastructure that supports the transition towards a low-carbon transport system in the United Kingdom (UK). The future hydrogen demand is forecasted over time using a logistic diffusion model, which reaches 50% of the market share by 2070. The problem is solved using an extension of SHIPMod, an optimisation-based framework that consists of a multi-period spatially-explicit mixed-integer linear programming (MILP) formulation. The optimisation model combines the infrastructure elements required throughout the different phases of the transition, namely economies of scale, road and pipeline transportation modes and carbon capture and storage (CCS) technologies, in order to minimise the present value of the total infrastructure cost using a discounted cash-flow analysis. The results show that the combination of all these elements in the mathematical formulation renders optimal solutions with the gradual infrastructure investments over time required for the transition towards a sustainable hydrogen economy.

Document type: Article

Enhancing the Financial Feasibility of PPP Projects with Hybrid Funding

Scipedia content — Wed, 03 Feb 2021 20:38:17 +0100

In transport infrastructure concessions, the sources of revenue to the private partner (or concessionaire) may include (i) the infrastructure users (e.g., tolling, in the case of roads), (ii) the government (e.g. through availability payments), and (iii) both users and government, which might be called a hybrid concession. An example of the latter is a road concession where the concessionaire is allowed to charge tolls to the road users but, because of relatively low revenues, the government agency might have to complement the toll revenue. This paper summarizes the cases where it may be justified for the government to complement users revenues and describes a model developed for the financial assessment of road concessions involving both tolling and government payments. The methodology described for roads can also be applied to other forms of transport infrastructure. A practical application of the model is demonstrated in the paper. For example, given traffic volumes and maximum acceptable toll rates for a particular road project, the model can be used to estimate the minimum availability payment that would be required for the project to attract private sector interest, that is, potential bidders in a competitive bidding scenario. The model can also be used to carry out sensitivity analyses of the impact of key input parameters on outputs such as the investors return on equity and annual debt service cover ratio.

PV-Alert: A fog-based architecture for safeguarding vulnerable road users

Scipedia content — Wed, 03 Feb 2021 20:30:27 +0100

International audience; High volumes of pedestrians, cyclists and other vulnerable road users (VRUs) have much higher casualty rates per mile; not surprising given their lack of protection from an accident. In order to alleviate the problem, sensing capabilities of smartphones can be used to detect, warn and safeguard these road users. In this research we propose an infrastructure-less fog-based architecture named PV-Alert (Pedestrian-Vehicle Alert) where fog nodes process delay sensitive data obtained from smartphones for alerting pedestrians and drivers before sending the data to the cloud for further analysis. Fog computing is considered in developing the architecture since it is an emerging paradigm that has paramount of advantages for low-latency applications which demand mobility support, geo-distribution and location awareness. We have also defined an algorithm for accident prediction and alerting traffic accidents involving vehicles and pedestrians. PV-Alert can be deployed quickly since it is based only on users' smartphones and doesn't require special infrastructure. Simulation results show that the proposed architecture is able to render alerts in real time whichever the wireless communication technology used to connect smartphones with fog nodes (Wi-Fi or LTE). Moreover, analytical and performance evaluations depict that the new architecture outperforms other related architectures in terms of reliability, scalability and latency.

Integrated One-Dimensional Modeling of Asphaltene Deposition in Wellbores/Pipelines

Scipedia content — Wed, 03 Feb 2021 20:29:15 +0100

—Asphaltene deposition in wellbores/pipelines causes serious production losses in the oil and gas industry. This work presents a numerical model to predict asphaltene deposition in\\ud wellbores/pipelines. This model consists of two modules: a Thermodynamic Module and a Transport Module. The Thermodynamic Module models asphaltene precipitation using the Peng-Robinson Equation of State with Peneloux volume translation (PR-Peneloux EOS). The Transport Module covers the modeling of fluid transport, asphaltene particle transport and asphaltene deposition. These\\ud modules are combined via a thermodynamic properties lookup-table generated by the Thermodynamic Module prior to simulation. In this\\ud work, the Transport Module and the Thermodynamic Module are first verified and validated separately. Then, the integrated model is\\ud applied to an oilfield case with asphaltene deposition problem where a reasonably accurate prediction of asphaltene deposit profile is\\ud achieved

Driver Behaviour Studies in the Motorway Operations Platform Grant

Scipedia content — Wed, 03 Feb 2021 20:22:31 +0100

This paper reports on a four-year project being undertaken in the U.K., which intends to address the causative mechanisms of motorway congestion, and how these may be overcome by the use of in-vehicle Intelligent Transportation Systems (ITS). The project comprises five studies, two focussing on driver behaviour and performance, and three on microscopic simulation and road operations. This paper provides an overview of progress made and work in progress in the former of these topics, in particular: (i) Phase 1: an instrumented vehicle study collecting microscopic time series on how drivers behave in slow moving dense traffic. An overview of results from this phase is presented; and (ii) Phase 2: to be initiated in late 2001, looks to examine how drivers behave when faced with the requirement for an emergency deceleration. The study will use a combination of a surrogate vehicle/test track approach and a fixed base driving simulator study, in order to examine the advantages of the differing methodologies and (if validity is proven) to increase database size. A brief review is given of the intended use of outputs from these studies in subsequent simulation modelling studies to be undertaken in future years.

An Efficient Approximation Algorithm for Traffic Engineering in Software Defined Networks

Scipedia content — Wed, 03 Feb 2021 20:21:22 +0100

Assessment System of Community Road based on the Spatial Dimension

Scipedia content — Wed, 03 Feb 2021 20:14:06 +0100

Enhance the sustainability of private land transport system at Ayer Keroh, Melaka

Scipedia content — Wed, 03 Feb 2021 20:01:50 +0100

yer Keroh Toll that under the administration of Hang Tuah Jaya Municipal Council (HTJMC) is the main entrance for the people to enter to the city from North-South Expressway. This situation causes congestion to happen in this area especially during weekend and holiday and lead to air pollution. Hence, it is important to solve this problem beginning with the transport system and brings the city toward the sustainable way by learning the foreign city experience. In this research, the researchers start to revise the case study from foreign city councils on what and how they improve their cities transport system in term of sustainability. There are total of 17 case studies been studied including the cities that recognize with Sustainable Transport Award (STA) and other special activity and event that held worldwide. These cases studied are merged with the behavioral modification. There are four methods of changing behavior: positive reinforcement, negative reinforcement, punishment and extinction. Besides, t...

Examining the relationships between individual’s time use and activity participations with their health indicators

Scipedia content — Wed, 03 Feb 2021 19:52:13 +0100

Purpose Using a three-week household activity-travel survey, this paper explores the relationship between individuals’ self-reported physical, mental and social health conditions and their time allocation for different types of in-home and out-of-home time activities. Methods A path model is developed to investigate the roles of activity-travel time use on the self-reported health conditions, while the socio-demographics and residential environment characteristics are also considered. Results The model results reveal heterogeneous impacts of different types of activities and intensities on individual’s self-reported health conditions. This study, however, did not find evidence of positive relationship between cycling and walking and self-reported physical health condition, which has been found in many developed countries. Presumably this is because in developing countries like Indonesia the individuals who walk and cycle are likely to be a part of economically disadvantaged groups who have less awareness to their own health conditions. Conclusion Beside activity and travel time use factors, age and working status were found significantly affecting the self-reported health conditions, regardless of respondents’ gender and income. Neighbourhood characteristics, such as population density, are also found positively correlated to self-reported respondents’ physical, social and mental health conditions.

Document type: Article

Encouraging Environmentally Friendly Driving Through Driver Assistance: The eCo Move Project

Scipedia content — Wed, 03 Feb 2021 19:51:38 +0100

questionnaire study was conducted in order to identify relevant driver motives and assistance options for environmentally-friendly driving. Eighteen participants rated items belonging to the three factors time, environment, and consumption, and subsequently evaluated three types of driver assistance systems. Results concerning the motives showed that older drivers (above the age of 65) focused significantly less on the time motive, whereas high annual mileage drivers tended to focus more on the time motive compared to low annual mileage drivers. Small vehicle drivers emphasized more on the environment motive compared to middle-class/van drivers. In terms of the driver assistance options for eco-friendly driving, a display of the current consumption rate through colorcoding received the highest number of first place rankings in the category intelligent vehicle information systems. A function that automatically shuts off the engine after a certain stopping time, as well as optimal gear choice and time to shift, were ranked high in the category intelligent advanced driver assistance systems. In the category intelligent navigation systems, a traffic- and situational adaptive navigation system was ranked the highest most often. Assessment of drivers’ preferences additionally showed that most participants preferred the assistance functions to provide visual information as opposed to direct intervention. The results concerning the driver groups and their underlying driving motives as well as the preference statements will be used to inform the design and development of assistance functions for promoting eco-driving within the European eCo Move project.

Erosion regularities of gas pipelines based on the gas-solid two-way coupling method

Scipedia content — Wed, 03 Feb 2021 19:50:29 +0100

In order to study the erosion regularities of pipelines with gas-solid flow and to predict the location where the maximum erosion occurs, the Eulerian-Lagrangian method was employed to calculate the gas-solid flow inner the pipeline. The gas phase flow field was calculated under the Eulerian coordinate system and the trajectory of particles were calculated under the Lagrangian coordinate system. The DNV erosion model and Forder et al. particle-wall collision model were used to calculate the erosion rate of the pipe wall. The two-way coupling method was taken into consideration in the process of numerical calculation. Multiple models are combined to study the erosion rate and the maximum erosion location of elbows under the conditions of five parameters which exert the most serious effect on erosion, including pipe diameter, particle diameter, inlet velocity, etc. The results show that: (1) the maximum erosion location of the pipe bend is sensitive with the change of the bend orientation, pipe diameter and...

One-to-One Matching of RTT and Path Changes

Scipedia content — Wed, 03 Feb 2021 19:37:58 +0100

Route selection based on performance measurements is an essential task in inter-domain Traffic Engineering. It can benefit from the detection of significant changes in RTT measurements and the understanding on potential causes of change. Among the extensive works on change detection methods and their applications in various domains, few focus on RTT measurements. It is thus unclear which approach works the best on such data. In this paper, we present an evaluation framework for change detection on RTT times series, consisting of: 1) a carefully labelled 34,008-hour RTT dataset as ground truth; 2) a scoring method specifically tailored for RTT measurements. Furthermore, we proposed a data transformation that improves the detection performance of existing methods. Path changes are as well attended to. We fix shortcomings of previous works by distinguishing path changes due to routing protocols (IGP and BGP) from those caused by load balancing. Finally, we apply our change detection methods to a large set of measurements from RIPE Atlas. The characteristics of both RTT and path changes are analyzed; the correlation between the two are also illustrated. We identify extremely frequent AS path changes yet with few consequences on RTT, which has not been reported before.

Comment: accepted and presented at ITC 29

HyperLoom

Scipedia content — Wed, 03 Feb 2021 19:37:42 +0100

Real-world scientific applications often encompass end-to-end data processing pipelines composed of a large number of interconnected computational tasks of various granularity. We introduce HyperLoom, an open source platform for defining and executing such pipelines in distributed environments and providing a Python interface for defining tasks. HyperLoom is a self-contained system that does not use an external scheduler for the actual execution of the task. We have successfully employed HyperLoom for executing chemogenomics pipelines used in pharmaceutic industry for novel drug discovery. 6 1

Stress analysis of vibrating pipelines

Scipedia content — Wed, 03 Feb 2021 19:33:27 +0100

The pipelines are subject to various constraints variable in time. Those vibrations, if not monitored for amplitude and frequency, may result in both the fatigue damage in the pipeline profile at high stress concentration and the damage to the pipeline supports. If the constraint forces are known, the system response may be determined with high accuracy using analytical or numerical methods. In most cases, it may be difficult to determine the constraint parameters, since the industrial pipeline vibrations occur due to the dynamic effects of the medium in the pipeline. In that case, a vibration analysis is a suitable alternative method to determine the stress strain state in the pipeline profile. Monitoring the pipeline vibration levels involves a comparison between the measured vibration parameters and the permissible values as depicted in the graphs for a specific pipeline type. Unfortunately, in most cases, the studies relate to the petrochemical industry and thus large diameter, long and straight pipel...

Hybrid modeling for vineyard harvesting operations

Scipedia content — Wed, 03 Feb 2021 19:32:31 +0100

Hiring workers under seasonal recruiting contracts causes significant variation of workers skills in the vineyards. This leads to inconsistent workers performance, reduction in harvesting efficiency, and increasing in grape losses rates. The objective of this research is to investigate how the variation in workers experience could impact vineyard harvesting productivity and operational cost. The complexity of the problem means that it is difficult to analyze the system parameters and their relationships using individual analytical model. Hence, a hybrid model integrating discrete event simulation (DES) and agent based modeling (ABM) is developed and applied on a vineyard to achieve research objective. DES models harvesting operation and simulates process performance, while ABM addresses the seasonal workers heterogeneous characteristics, particularly experience variations and disparity of working days in the vineyard. The model is used to evaluate two seasonal recruiting policies against vineyard productivity, grape losses quantities, and total operational cost.

Electric vehicles energy management using direct torque control — space vector pulse width modulation combined to polynomial controllers

Scipedia content — Wed, 03 Feb 2021 19:27:49 +0100

International audience; This paper describes an energy management strategy for an electric vehicle (EV). The proposed EV architecture contains a pack of the batteries which presents the energy source and a pack of the supercapacitors (SC) used as power source. The pack of the batteries produces the necessary energy to move forward the vehicle while the pack of the SC produces the lacking power in acceleration and in braking phases. Two DC-DC converters are used to interface the energy sources with the DC-bus. A bidirectional DC-AC converter is used to connect the traction motor to the DC-bus. The proposed control method is focused on the power flow management within the EV depending on electrical behavior of the energy sources. The validity of the proposed control strategy is proofed through some reduced scale simulations tests using the New European Driving Cycle (NEDC).

Characterizing Driving Context from Driver Behavior

Scipedia content — Wed, 03 Feb 2021 19:22:46 +0100

Because of the increasing availability of spatiotemporal data, a variety of data-analytic applications have become possible. Characterizing driving context, where context may be thought of as a combination of location and time, is a new challenging application. An example of such a characterization is finding the correlation between driving behavior and traffic conditions. This contextual information enables analysts to validate observation-based hypotheses about the driving of an individual. In this paper, we present DriveContext, a novel framework to find the characteristics of a context, by extracting significant driving patterns (e.g., a slow-down), and then identifying the set of potential causes behind patterns (e.g., traffic congestion). Our experimental results confirm the feasibility of the framework in identifying meaningful driving patterns, with improvements in comparison with the state-of-the-art. We also demonstrate how the framework derives interesting characteristics for different contexts, through real-world examples.

Comment: Accepted to be published at The 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2017)

Jamming and Spoofing Protection for ADS-B Mode S Receiver Through Array Signal Processing

Scipedia content — Wed, 03 Feb 2021 19:22:04 +0100

International audience; Automatic-dependent surveillance-broadcast (ADS-B) receivers are vulnerable to jamming and spoofing attacks. Air traffic management is expected to heavily rely on ADS-B in the future so it is important to provide protection against these attacks. One promising solution is array signal processing. Jamming signals can be suppressed by beamforming and ADS-B positions can be verified by comparing them to the measured angles of arrival (AoAs). Many studies have been done on this topic but they generally consider either jamming or spoofing. However, in a real environment, anti-jamming and anti-spoofing functions must be provided together. It is important to understand the performance when these two functions are implemented simultaneously in order to guide future research and development strategies and implementation plans. Thus, we conducted an experimental evaluation of anti-jamming and anti-spoofing functions. For jamming protection, a power-inversion beamformer was used to suppress the jamming signal. For spoofing protection, a Capon’s beamformer was used to measure the AoA. The array used was a uniform linear array of four elements. The experiments were conducted in an anechoic chamber using a four-channel oscilloscope and the signal processing was conducted offline. The results of the anti-jamming experiment showed that the jammed signals were successfully recovered and the signal-to-jamming-plus-noise (SJN) ratio was increased to above the decodable level. The effects of various parameters on the overall performance and the lower bound performance were also investigated. Moreover, the anti-spoofing experiment showed that the AoA of the ADS-B signal could be measured successfully. The AoA accuracy was evaluated in terms of the standard deviation, which was further converted into the probability of spoofing detection. These findings will be important in the implementation of effective infrastructure to ensure safe air travel.

Development and evaluation of two learning-based personalized driver models for car-following behaviors

Scipedia content — Wed, 03 Feb 2021 19:21:16 +0100

Personalized driver models play a key role in the development of advanced driver assistance systems and automated driving systems. Traditionally, physical-based driver models with fixed structures usually lack the flexibility to describe the uncertainties and high non-linearity of driver behaviors. In this paper, two kinds of learning-based car-following personalized driver models were developed using naturalistic driving data collected from the University of Michigan Safety Pilot Model Deployment program. One model is developed by combining the Gaussian Mixture Model (GMM) and the Hidden Markov Model (HMM), and the other one is developed by combining the Gaussian Mixture Model (GMM) and Probability Density Functions (PDF). Fitting results between the two approaches were analyzed with different model inputs and numbers of GMM components. Statistical analyses show that both models provide good performance of fitting while the GMM--PDF approach shows a higher potential to increase the model accuracy given a higher dimension of training data.

A Configurable Framework for Hough-Transform-Based Embedded Object Recognition Systems

Scipedia content — Wed, 03 Feb 2021 19:16:48 +0100

Real-time object recognition on low-power embedded devices is a widely requested task, needed in manifold applications. However, it is still a demanding challenge to achieve desired performance goals. For example, for advanced driver assistance systems (ADAS) or autonomously driven cars, object recognition and lane detection are indispensable tasks. Another field of application is the continuous retrieval of the construction progress on-site for validation of the construction site status, by detecting installed components using a given CAD model. This paper presents a framework for highly customizable object detection systems implemented on a single heterogeneous computing chip leveraging FPGA logic and standard processors. The FPGA logic is used to implement a custom variation of the Hough Transform and further image processing tasks efficiently. The dedicated logic is supplemented with a software stack, which consists of a Linux operating system, including hardware access drivers, as well as high-level libraries like OpenCV and Robot Operating System (ROS) - all running on the same device. The capabilities of the system are demonstrated for three application scenarios, namely race track recognition, lane recognition and object detection tasks performed within a construction assistance system.

Optimized and enhanced grid architecture for electric vehicles in Europe

Scipedia content — Wed, 03 Feb 2021 19:16:19 +0100

For an optimized large-scale roll-out of EVs in Europe whilst at the same time maximizing the potential of DER integration, an optimized and enhanced grid architecture for EVs in Europe has to be considered. The work in this paper is addressing this topic and summarizing the corresponding project findings. The aim of this approach is to provide a framework for the further investigation of selected use cases which allows implementing and comparing scenarios of different DSOs. Following a Smart Grid approach, the developed grid architecture implements energy grid entities and ICT components. The general framework was described including all its relevant clusters and indicating related entities. The network types used for this architecture are following the SGAM and Smart Grid Standards Map approach. A so-called “Smart Grid Connection Point”, which is a generic system interface, is used in this work to allow a more simplified graphical architecture model and increase its readability. Similar to the concept and purpose of the Smart Grid Connection Point, also the principle of an integration bus for entity clusters was introduced. From the Integration bus, the information from/to external systems passes through the Smart Grid Connection Point using one of a range of possible technological options. The position of EVs charging infrastructure within the framework is defined at the border between the domains DERs (generation) and consumption, which takes into account future V2G scenarios, where EVs may act as consumption and generation devices. EVSEs and DERs may be connected as standalone systems directly to the grid, or indirectly as part of one of the clusters at the customer premises domain which refers to the three location-wise types of charging, public, semi-public and private charging. Regarding controlled charging of EVs this optimized architecture allows a variety of different local, distributed or aggregated options which may involve different types of actors. European Commission's FP7

No need to learn from each other?: Potentials of Knowledge Modeling in Autonomous Vehicle Systems Engineering

Scipedia content — Wed, 03 Feb 2021 19:15:36 +0100

International audience; Engineering autonomous driving functions has become a dramatic challenge in automotive engineering since it is now required to integrate knowledge from multi-disciplinary domains. In this context, the widespread engineering methods are showing their limit since they mainly integrate technological centered point of view. Thus, these new requirements lead naturally to the design of new method for engineering in automotive field. The goal of this paper is to sketch an overview of the possible improvements that Knowledge Modeling and ontologies can bring to Systems Engineering and especially in the case of Autonomous Driving functions.

Document type: Conference object

THE BARRIERS IN THE IMPLEMENTATION PROCESS AND THE OPERATION OF INNOVATIVE URBAN TRANSPORT: THE CASE OF BRT JAKARTA

Scipedia content — Wed, 03 Feb 2021 19:14:30 +0100

A Programmable SDN+NFV-based Architecture for UAV Telemetry Monitoring

Scipedia content — Wed, 03 Feb 2021 19:06:43 +0100

The explosive growth in the worldwide use of\\ud Unmanned Aerial Vehicles (UAVs) has raised a critical concern\\ud with respect to the adequate management of their ad hoc network\\ud configuration as required by their mobility management process.\\ud As UAVs migrate among ground control stations, associated\\ud network services, routing and operational control must also\\ud rapidly migrate to ensure a seamless transition. In this paper,\\ud we present a novel, lightweight and modular architecture which\\ud supports high mobility and situational-awareness through the\\ud application of Software Defined Networking (SDN) and Network\\ud Function Virtualization (NFV) principles on top of the UAV\\ud infrastructure. By combining SDN+NFV programmability we\\ud can achieve a robust migration of UAV-related network services,\\ud such as network monitoring and anomaly detection as well as\\ud smooth UAV migration that confronts high mobility requirements.\\ud The proposed container-based monitoring and anomaly detection\\ud Network Functions (NFs) as employed within our architecture\\ud can be tuned to specific UAV types providing operators better\\ud insight during live, high-mobility deployments. We evaluate our\\ud architecture against telemetry from over 80 flights from a\\ud scientific research UAV infrastructure showing our ability to tune\\ud and detect emerging challenges.

Learning Less is More - 6D Camera Localization via 3D Surface Regression

Scipedia content — Wed, 03 Feb 2021 19:05:10 +0100

Popular research areas like autonomous driving and augmented reality have renewed the interest in image-based camera localization. In this work, we address the task of predicting the 6D camera pose from a single RGB image in a given 3D environment. With the advent of neural networks, previous works have either learned the entire camera localization process, or multiple components of a camera localization pipeline. Our key contribution is to demonstrate and explain that learning a single component of this pipeline is sufficient. This component is a fully convolutional neural network for densely regressing so-called scene coordinates, defining the correspondence between the input image and the 3D scene space. The neural network is prepended to a new end-to-end trainable pipeline. Our system is efficient, highly accurate, robust in training, and exhibits outstanding generalization capabilities. It exceeds state-of-the-art consistently on indoor and outdoor datasets. Interestingly, our approach surpasses existing techniques even without utilizing a 3D model of the scene during training, since the network is able to discover 3D scene geometry automatically, solely from single-view constraints.

Comment: CVPR 2018

Study on the propagation and dissipation of inland ship congestion under different control strategies

Scipedia content — Wed, 03 Feb 2021 19:01:02 +0100

Inland waterway transportation is an important part of the comprehensive transportation system of sustainable development, and it is also a way of transportation which is restricted by natural conditions greatly. In recent years, the problems of insufficient traffic capacity of The Three Gorges become prominent due to the increasing in the number of ships. And the ship’s detention caused by gale, frog, accident and one-way traffic in dry season has occurred, which not only increased the pressure of the navigable waterway but also seriously affected the safety of shipping. Based on the different types of ships, the Arena software was used to simulate the ship traffic flow. The paper analyzed the traffic congestion propagation and dissipation rule of the ship under different navigation control methods, and provided decision reference for the navigation management department to formulate the relevant navigation control strategy.

How Close Can I Be? - A Comprehensive Analysis of Cellular Interference on ATC Radar

Scipedia content — Wed, 03 Feb 2021 18:58:56 +0100

Increasing data traffic demands over wireless spectrum have necessitated spectrum sharing and coexistence between heterogeneous systems such as radar and cellular communications systems. In this context, we specifically investigate the co-channel coexistence between an air traffic control (ATC) radar and a wide area cellular communication (comms) system. We present a comprehensive characterization and analysis of interference caused by the comms system on the ATC radar with respect to multiple parameters such as radar range, protection radius around the radar, and radar antenna elevation angle. The analysis suggests that maintaining a protection radius of 50 km around the radar will ensure the required INR protection criterion of -10 dB at the radar receiver with ~0.9 probability, even when the radar beam is in the same horizon as the comms BS. Detailed evaluations of the radar target detection performance provide a framework to choose appropriate protection radii around the radar to meet specific performance requirements.

Comment: This paper has been submitted to IEEE Globecom 2017

Time mobility

Scipedia content — Wed, 03 Feb 2021 18:58:13 +0100

International audience

A Standard Mission Profile for Hybrid-Electric Regional Aircraft based on Web Flight Data

Scipedia content — Wed, 03 Feb 2021 18:57:15 +0100

To reduce emissions of air traffic, future aircraft will install hybrid-electric propulsion systems. We require the load conditions over the time in service, to design these aircraft. In this paper, we propose a mission profile for a regional aircraft with a hybrid-electric propulsion system. We focused on regional aircraft, which are in service in Ireland and the United Kingdom (UK). The reference aircraft ATR\\,72-600 is a turboprop aircraft with a capacity of 70 passengers. To propose a mission profile, we have analyzed more than 6000 flights of four different aircraft of the same type. Input data is provided by online databases, which collect flight data. We are able to show that the maximum available power is needed for about 52 seconds during take-off and climb phase of the flight. The median flight time is 59 minutes and 30 seconds. The average required power is 53\\,\\% of the maximum power. The average traveled distance is 407\\,km, which is less than one third of the aircraft's maximum reach. These findings are needed for calculating the lifetime of drivetrain components of a hybrid or all electric aircraft. In our further work, we will design an electric machine for regional aircraft. This mission profile will be used to design different power train components.

A Survey on Urban Traffic Optimisation for Sustainable and Resilient Transportation Network

Scipedia content — Wed, 03 Feb 2021 18:56:37 +0100

Nowadays, sustainability and resilience have become a major consideration that cannot be neglected in urban development. People are starting to consider utilizing the urban infrastructure environment to maintain and improve the functionality and availability of the urban system when unexpected events take place. Traffic congestion is always a major issue in urban planning, especially when the vehicles in the roadway keep growing and the local authorities are lack of solutions to manage or distribute the traffics in the city. It has huge impact on urban sustainability and resilience such as overload of the city’s infrastructure, and air pollution, etc. This paper presents a survey on the challenges of developing sustainable and resilient transportation networks and the current urban traffic optimisation methods, as a possible solution to address such challenges. It aims to describe and define the state of the art on the research on sustainable and resilient transportation networks in urban development and a taxonomy of different traffic optimisation methods used for avoiding traffic congestion and improve urban traffic management.

Low-Latency Routing on Mesh-Like Backbones

Scipedia content — Wed, 03 Feb 2021 18:55:16 +0100

Early in in the Internet's history, routing within a single provider's WAN centered on placing traffic on the shortest path. More recent traffic engineering efforts aim to reduce congestion and/or increase utilization within the status quo of greedy shortest-path first routing on a sparse topology. In this paper, we argue that this status quo of routing and topology is fundamentally at odds with placing traffic so as to minimize latency for users while avoiding congestion. We advocate instead provider backbone topologies that are more mesh-like, and hence better at providing multiple low-latency paths, and a routing system that directly considers latency minimization and congestion avoidance while dynamically placing traffic on multiple unequal-cost paths. We offer a research agenda for achieving this new low-latency approach to WAN topology design and routing.

A new trans-Atlantic route structure for strategic flight planning over the NAT airspace

Scipedia content — Wed, 03 Feb 2021 18:49:13 +0100

International audience; Air traffic across the North Atlantic airspace has witnessed an incessant increase over the last decades. However, the efficiency of trans-Atlantic air traffic management is still low nowadays due to the limited radar coverage. Automated Dependent Surveillance-Broadcast systems represents an opportunity to enhance the strategic flight planning over the oceans by reducing separation standards between aircraft. Besides, the strong winds present a challenge for oceanic flights. Therefore, flying on the wind-optimal routes will save significantly both fuel and time. In this paper, we propose a new trans-Atlantic route structure that benefits from the jetstreams in order to construct wind-optimal flight trajectories. Then, we introduce an optimization model for detecting and resolving conflicts. The analysis is carried out on real traffic data to prove the efficiency of the proposed method. Experimental findings show an improvement in terms of conflict resolution and induced delays.

Technological and Operational Scenarios on Aircraft Fleet-Level towards ATAG and IATA 2050 Emission Targets

Scipedia content — Wed, 03 Feb 2021 18:48:11 +0100

In the face of global climate change various private and public stakeholders of the commercial aviation industry have proclaimed ambitious goals aimed at reducing the global fuel consumption and thus mitigating the future environmental impact of aviation by halving aviation´s fleet-level emissions by 50 % compared to year 2005. Here, the potential of aircraft technologies, production ramp-ups and operational improvement options are assessed to quantify the global fleet-level emissions up to the year 2050. Based on the estimation of impact of next-generation aircraft types with market entries until 2020, fifteen fleet-level emission scenarios based on various technology, production and operational scenarios with their single contribution towards long-term emission goal, are the objectives of this paper. A numerical model of the global air transport fleet is employed to quantify the fleet-wide fuel demand and carbon-emissions reduction impact and conduct sensitivity analyses. New aircraft technologies together with up to radical ramp-up timelines might lower fleet-level fuel burn until year 2050 between -17 % to -27 %. Increasing aircraft productivity by increasing loadfactors, installed seats and increased aircraft utilisation further reduce fleet-level fuel burn until year 2050 by -7 % to -8 %. The application of retrofit solutions for in-fleet aircraft can reduce the fleet-level fuel burn until year 2050 by around -3 %. Halving regional RPK growth rates might lead to fleet-level fuel burn reductions by around -6% until year 2050. The results obtained clearly indicate that the climate goals cannot be reached solely by following long-term research goals for aircraft technology improvements, because of slowing effects on fleet level. Even following the long-term research goals for aircraft technology improvements combined with radical production ramp-ups and significant improvements in aircraft productivities will lead to a carbon- neutral growth until year 2050 but at roughly 10% higher emission compared to the IATA goals until year 2035.

Behavioural Change Support Intelligent Transportation Applications

Scipedia content — Wed, 03 Feb 2021 18:38:31 +0100

This workshop invites researchers and practitioners to participate in exploring behavioral change support intelligent transportation applications. We welcome submissions that explore intelligent transportation systems (ITS), which interact with travelers in order to persuade them or nudge them towards sustainable transportation behaviors and decisions. Emerging opportunities including the use of data and information generated by ITS and users' mobile devices in order to render personalized, contextualized and timely transport behavioral change interventions are in our focus. We invite submissions and ideas from domains of ITS including, but not limited to, multi-modal journey planners, advanced traveler information systems and in-vehicle systems. The expected outcome will be a deeper understanding of the challenges and future research directions with respect to behavioral change support through ITS.

Comment: Intelligent Transportation Systems Conference (ITSC) 2017 Worksho

What is a Learning Town? Reflections on the Experience at Wirksworth

Scipedia content — Wed, 03 Feb 2021 18:34:29 +0100

This paper explores the legacy of regeneration project work and knowledge management and transfer as a result of intervention through a charity designed to support new business opportunities, specifically in arts and entertainment, tourism, skills development and training. As part of the University of Derby’s own work-related learning and problem-based learning, a project team was assigned to work alongside the charity ‘New Opportunities in Wirksworth!’ (NOW!). A participant observation, action research approach has been used to elicit and analyse the knowledge transfer, both explicit and implicit. Staff and students from the University of Derby have been contracted to research tourism development specifically in festival supply and demand, the attractiveness of the destination and its key features the market, mining heritage and volunteer railway. Staff and students also committed to an events strategy, marketing the destination and finance for start-ups. The University is engaged in tacit and explicit knowledge transfers. Key stakeholders have reflected on a decade of achievements and both fails and success stories. Agendas for the future have been identified and the project NOW! Has a legacy of both tacit and explicit knowledge for the benefit of other communities. There is an ongoing desire to explore how both public and private sectors can benefit from knowledge sharing and to benefit ongoing problem-based learning in education and training.

Document type: Conference object

Open source tools for locomotion and apprehension of space by visually impaired persons: some propositions to build a prototype based on Arduino, speech recognition and OpenStreetMap

Scipedia content — Wed, 03 Feb 2021 18:33:44 +0100

International audience; In this article, we discuss about the benefit of IoT for people with disabilities, particularly for visually impaired and blind people mobility. We propose a simple prototype using OpenStreetMap data combined to physical environment data measured from sensors connected to a Arduino board through Speech recognition.

An offshore energy simulation through flow networks: CEL within the MSP Challenge 2050 simulation game platform

Scipedia content — Wed, 03 Feb 2021 18:32:38 +0100

This paper presents the design of the offshore energy simulation CEL as a flow network, and its integration in the MSP Challenge 2050 simulation game platform. This platform is designed to aid learning about the key characteristics and complexity of marine or maritime spatial planning (MSP). The addition of CEL to this platform greatly AIDS MSP authorities in learning about and planning for offshore energy production, a highly topical and big development in human activities at sea. Rather than a standard flow network, CEL incorporates three additions to accommodate for the specificities of energy grids: an additional node for each team's expected energy, a split of each node representing an object into input and output parts to include the node's capacity, and bidirectional edges for all cables to enable more complex energy grid designs. Implemented with Dinic's algorithm it takes less than 30ms for the simulation to run for the average amount of grids included in an MSP Challenge 2050 game session. In this manner CEL enables MSP authorities and their energy stakeholders to use MSP Challenge 2050 for designing and testing more comprehensive offshore energy grids.

Analysis on logistic company action toward the access restriction policy on freight vehicle

Scipedia content — Wed, 03 Feb 2021 18:32:23 +0100

The high volume of freight vehicles that enters, leaves or passes through the urban areas, especially Jakarta, has caused traffic congestion. Local authority plans to perform the access restriction on freight vehicles on the Jakarta Outer Ring Road (JORR) to reduce the congestion on that toll road. The study aims to analyze the alternative solutions of the logistics companies to overcome the impact of such policy. The data collection is done by interviewing 102 truck drivers and 7 staffs of logistic companies that use JORR. The results show that the most preferred action is shifting the operating time. Based on the open test, access restriction policy on JORR may cause a significant impact on the operational costs of delivery. Shifting the operational time will increase the operating cost by 1.71%, while turning the route will increase the operating costs by 4.35%. Moreover, changing the mode will reduce the operating expenses by 50%, and the combination action of shifting the route and the time will incr...

Alternative Trajectory Options for Delay Reduction in Demand and Capacity Balancing

Scipedia content — Wed, 03 Feb 2021 18:31:08 +0100

ming to a more collaborative demand and capacity balancing (DCB), in the scope of trajectory based operations, this paper presents an approach that takes alternative trajectories into a DCB optimization algorithm. These alternative trajectories are generated by the airspace users for those flights traversing hotspots (i.e. sectors with demand above capacity), which are predicted by the Network Manager. The trajectories consider lateral re-routings and/or vertical avoidance of all detected hotspots, which, along with different types of delay measures (including linear holding and in-flight delay recovery), are then integrated as a whole into a centralized optimization model to manage the traffic flow under a set of static scheme of airspace capacities. The combination of trajectory options and distribution of delays are hence optimized with the objective of minimizing the total deviation with regard to airspace users’ preferences (taking into account the fuel consumption, route charge and the cost of delay). Results suggest that delays can be remarkably reduced once alternative trajectory options are included in the DCB algorithm. Nevertheless, this delay reduction is obtained by diverting a large number of flights, yielding to an interesting trade-off between environmental impact and cost-efficiency for the airspace users.

Peer Reviewed

Including linear holding in air traffic flow management for flexible delay handling

Scipedia content — Wed, 03 Feb 2021 18:27:48 +0100

This is an author final draft version of published work that can be found at: https://arc.aiaa.org/doi/10.2514/1.D0081 Copyright © 2018 by Yan Xu and Xavier Prats. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the ISSN 2380-9450 (online) to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp.

This paper introduces a strategy to include linear holding into air traffic flow management initiatives, together with the commonly used ground holding and airborne holding measures. In this way, flow management performance can be improved when handling delay assignment with uncertainty. First, a trajectory generation method is presented, aiming at computing, per flight, the maximum linear holding realizable using the same fuel as the original nominal flight. This information is assumed to be computed and shared by the different airlines and it is then used to build a network air traffic flow management model to optimally assign delays, in the scope of trajectory-based operations. Hence, the best distribution of delay is optimized at given positions along the flight trajectory (combining the three holding practices together) and taking into account the cost of delay, especially in the fuel consumption. The problem is formulated as a mixed integer linear program and solved with a commercial off-the-shelf solver. An illustrative example is given, showing that under the circumstance of capacity recovered ahead of schedule, including linear holding contributes to a notable delay reduction compared with the case where only ground and airborne holding apply. Read More: https://arc.aiaa.org/doi/10.2514/1.D0081

Peer Reviewed

Proposing bat inspired heuristic algorithm for the optimization of GMPLS networks

Scipedia content — Wed, 03 Feb 2021 18:22:06 +0100

Introduction of modern and diverse applications in telecommunication field has raised challenges in networking area regarding efficient use of network resources and with optimizing performance. Therefore MPLS/GMPLS (Generalized multiprotocol label switching) networks were introduced to provide a better quality of service to meet users' requirements as well as to optimize network resources. GMPLS networks use traffic engineering techniques for more efficient communication within the network and help to optimize network resources. This paper proposes BAT inspired metaheuristic algorithm for selecting an efficient route in MPLS/ GMPLS networks. In our investigation we considered routing costs as an objective function with goal to minimize it. The paper uses BAT algorithm with various levels of loudness parameter. The simulation results show performance improvements in MPLS/GMPLS networks of different size.

Document type: Conference object

On Canonical Polyadic Decomposition of Non-Linear Gaussian Likelihood Functions

Scipedia content — Wed, 03 Feb 2021 18:17:35 +0100

Non-linear filtering arises in many sensor applications such as for instance robotics, military reconnaissance, advanced driver assistance systems and other safety and security data processing algorithms. Since a closed-form of the Bayesian estimation approach is intractable in general, approximative methods have to be applied. Kalman or particle based approaches have the drawback of either a Gaussian approximation or a curse of dimensionality which both leads to a reduction in the performance in challenging scenarios. An approach to overcome this situation is state estimation using decomposed tensors. In this paper, a novel method to compute a non-linear likelihood function in Canonical Polyadic Decomposition form is presented, which avoids the full expansion of the discretized state space for each measurement. An exemplary application in a radar scenario is presented.

Kafka interfaces for composable streaming genomics pipelines

Scipedia content — Wed, 03 Feb 2021 18:16:41 +0100

Modern sequencing machines produce order of a terabyte of data per day, which need subsequently to go through a complex processing pipeline. The conventional workflow begins with a few independent, shared-memory tools, which communicate by means of intermediate files. Given its lack of robustness and scalability, this approach is ill-suited to exploiting the full potential of sequencing in the context of healthcare, where large-scale, population-wide applications are the norm. In this work we propose the adoption of stream computing to simplify the genomic resequencing pipeline, boosting its performance and improving its fault-tolerance. We decompose the first steps of the genomic processing in two distinct and specialized modules (preprocessing and alignment) and we loosely compose them via communication through Kafka streams, in order to allow for easy composability and integration in the already-existing YARN-based pipelines. The proposed solution is then experimentally validated on real data and shown to scale almost linearly.

Fault injection method for safety and controllability evaluation of automated driving

Scipedia content — Wed, 03 Feb 2021 18:14:16 +0100

dvanced Driver Assistance Systems (ADAS) and automated vehicle applications based on embedded sensors have become a reality today. As road vehicles increase its autonomy and the driver shares his role in the control loop, novel challenges on their dependability assessment arise. One key issue is that the notion of controllability becomes more complex when validating the robustness of the automated vehicle in the presence of faults. This paper presents a simulation-based fault injection approach aimed at finding acceptable controllability properties for the model-based design of control systems. We focus on determining the best fault models inserting exceptional conditions to accelerate the identification of specific areas for testing. In our work we performed fault injection method to find the most appropriate safety concepts, controllability properties and fault handling strategies at early design phases of lateral control functions based on the error in the Differential GPS signal. Authors wants to thank to the H2020 UnCoVerCPS Project (with grant number 643921) and the ECSEL JU AMASS project under H2020 grant agreement No 692474 and from MINETUR (Spain).

Analyzing and managing the slot occupancy of car parking by exploiting vision-based urban surveillance networks

Scipedia content — Wed, 03 Feb 2021 18:09:46 +0100

In this paper, we present an approach for the analysis of parking slots by exploiting urban surveillance networks. This work has been developed in a project which aims to facilitate to the car drivers the access to available car parking slots. This paper describes a framework that exploits video streams provided by urban networks of cameras. The objective is to remotely determine the occupancy status of parking slots. Besides, the paper presents a case study and a discussion about a broadcasting strategy that could be used to share the positions of identified vacant parking slots with drivers searching an available parking slot.

Health impact modelling of different travel patterns on physical activity, air pollution and road injuries for São Paulo, Brazil

Scipedia content — Wed, 03 Feb 2021 18:07:58 +0100

Background São Paulo city, Brazil, faces challenges caused by rapid urbanization. We illustrate how future travel patterns could lead to different health consequences in the city. Methods We evaluated the health impacts of different travel pattern scenarios for the São Paulo adult population by comparing the travel patterns of São Paulo in 2012 with counterfactual scenarios in which the city adopted travel patterns of i) those living in the city's expanded centre; ii) London (2012); iii) a highly motorized São Paulo (SP California); and iv) a visionary São Paulo (SP 2040), with high levels of walking and cycling and low levels of car and motorcycle use. For each scenario we estimated changes in exposure to air pollution, road injury risk, and physical activity. Health outcomes were estimated using disability adjusted life years (DALYs) and premature deaths averted. Sensitivity analyses were performed to identify the main sources of uncertainty. Results We found considerable health gains in the SP 2040 scenario (total 63.6 k DALYs avoided), with 4.7% of premature deaths from ischemic heart disease avoided from increases in physical activity alone. Conversely, we found substantial health losses in the scenario favouring private transport (SP California, total increase of 54.9 k DALYs), with an increase in road traffic deaths and injuries among pedestrians and motorized vehicles. Parameters related to air pollution had the largest impact on uncertainty. Conclusions Shifting travel patterns towards more sustainable transport can provide major health benefits in São Paulo. Reducing the uncertainties in the findings should be a priority for empirical and modelling research on the health impacts of such shifts.

Highlights • There is scarce evidence of transportation impacts on health in developing cities • Comparative risk assessment used to assess impacts on three major risk factors • We found large net health gains in sustainable transport scenario for Sao Paulo, Brazil • We also found large net health losses in a car dependent scenario for Sao Paulo • Physical activity provided the largest health impacts, similar to previous studie

Document type: Article

Efficient graph-based V2V free space fusion

Scipedia content — Wed, 03 Feb 2021 18:06:27 +0100

necessary prerequisite for future driver assistance systems as well as automated driving is a suitable and accurate representation of the environment around the vehicle with a sufficient range. To extend the range of the environment representation, sharing the environment detections of multiple vehicles via vehicle-to-vehicle (V2V) communication is a promising approach. In this paper, we present a method to fuse shared free space detections from multiple vehicles. The detections are represented as Parametric Free Space (PFS) maps, which are especially suitable for real-time radio V2V-transmission due to their compactness. A graph-based algorithm to fuse PFS maps is proposed that solves possible contradictions between the maps and incorporates the maps' uncertainty attributes. By solely operating on the contour, the fusion can be carried out by a simple path search in a fusion graph that is constructed from the maps. This results in an efficient method that finds the fusion result within few iterations. To account for possible errors in the relative poses between the PFS maps, we furthermore present an adapted Iterative Closest Point (ICP) matching to align the maps before the fusion. Therein we employ a modified soft-assign scheme for robust outlier rejection, and incorporate the PFS maps' boundary orientation to improve the matching process. We show the capabilities of our method by presenting results on real test drive data.

The Case for Making Tight Control Plane Latency Guarantees in SDN Switches

Scipedia content — Wed, 03 Feb 2021 18:04:34 +0100

SDN controllers demand tight performance guarantees over the control plane actions performed by SDN switches. For example, traffic engineering techniques that frequently reconfigure the network require guarantees on the speed of gathering data from the network and the speed of reconfiguring the network. Yet, modern switches provide no guarantees for these control plane actions, e.g., inserting rules or gathering statistics. In fact, initial experiments demonstrate that unpredictability in control plane actions, specifically rule insertion, can inflate application completion times by a factor of 4X! In this paper, we present Mercury, a framework that offers a novel method for efficiently and practically managing switch TCAM to enable strict performance guarantees. Specifically, Mercury builds on the fundamental properties of TCAMs and provides guarantees by trading-off a nominal amount of TCAM space for assured performance. Our preliminary evaluations show that with less than 10% overheads, Mercury provides guarantees of 10ms insertion time and improves application performance by a factor 2X to 5X.

A rapid prototyping environment for cooperative Advanced Driver Assistance Systems

Scipedia content — Wed, 03 Feb 2021 18:01:14 +0100

dvanced Driver Assistance Systems (ADAS) were strong innovation drivers in recent years, towards the enhancement of traffic safety and efficiency. Today’s ADAS adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. However, to further enhance their benefit, ADAS need to cooperate in the future, using communication technologies. The resulting combination of vehicle automation and cooperation, for instance, enables solving hazardous situations by a coordinated safety intervention on multiple vehicles at the same point in time. Since the complexity of such cooperative ADAS grows with each vehicle involved, very large parameter spaces need to be regarded during their development, which necessitate novel development approaches. In this paper, we present an environment for rapidly prototyping cooperative ADAS based on vehicle simulation. Its underlying approach is either to bring ideas for cooperative ADAS through the prototyping stage towards plausible candidates for further development or to discard them as quickly as possible. This is enabled by an iterative process of refining and assessment. We reconcile the aspects of automation and cooperation in simulation by a tradeoff between precision and scalability. Reducing precise mapping of vehicle dynamics below the limits of driving dynamics enables simulating multiple vehicles at the same time. In order to validate this precision, we also present a method to validate the vehicle dynamics in simulation against real world vehicles. DFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität Berlin

Document type: Article

Dynamic Bus Rapid Transit (BRT) Resource Management Modeling Using Fuzzy Logic Paradigm

Scipedia content — Wed, 03 Feb 2021 17:43:00 +0100

Our prosperity and well-being are founded on efficient access to goods, services, people and places. In many developing countries, inadequate transport facilities are often the norm rather than the exception. A good transport system is essential to support economic growth and development. Nowadays, Traffic congestion resulting into excessive waiting time for the commuter is one of the leading causes of lost productivity and decreased standard of living in metropolis, urban and rural sectors in cities all over the world. This work employed a soft system methodology that is fuzzy logic-based traffic control modeling technique to predict traffic conditions and propose a flexible approach to resolving the allocation of Buses. The technique involves the fuzzification of input variables that is based on major traffic conditions such as, (Day of the week, Time of the day, public holidays, weather conditions and locality). The design employed Mamdanistyle inference system which is very good for the representation of human reasoning and effective analysis. The implementation is done using MATLAB 7.0 fuzzy logic tools. The result shows a tool that can be effectively used to analyze potential traffic deadlock conditions in Lagos State, Nigeria and help traffic officials in the city improve productivity cum standard of living in Lagos metropolis.

Traffic Responsive Intersection Control Algorithm Using GPS Data

Scipedia content — Wed, 03 Feb 2021 17:40:40 +0100

This paper reports on the performance of signalised intersection control using vehicle GPS information compared to fixed-time and inductive loop based control. Traffic congestion forecasts estimate an increase of about 60% in 2030. At present, poor choice of signal timings by isolated intersection controllers cause traffic delays that have enormous negative impacts on the economy and environment. Signal timings can be improved by using vehicles' GPS information to overcome the control action deficit at isolated intersections. This new signal control algorithm is beneficial for traffic engineers and governmental agencies, as traffic flow can be optimised and, hence, fuel consumption and emissions decreased. Under the open European Telecommunication Standards Institute (ETSI) Cooperative Awareness Message (CAM) framework, a traffic responsive GPS based vehicle actuation algorithm (GPS-VA) is proposed. GPS-VA uses position and heading data from vehicle status broadcasts, and inferred velocity information to determine vehicle queue lengths and detect vehicles passing through the intersection. The gathered information is then used to actuate intersection signal timings. Microscopic simulations comparing GPS-VA to fixed-time control and inductive loop based vehicle actuation (Loop-VA) on four urban road networks were performed to see how the proposed GPS-VA algorithm performs compared to existing control strategies. The results show that the GPS-VA is an effective alternative to traditional intersection control strategies, offering delay reductions of up to 50% for connected vehicle fleet penetrations above 30%.

Impact of mobility-on-demand on traffic congestion: Simulation-based study

Scipedia content — Wed, 03 Feb 2021 17:36:53 +0100

The increasing use of private vehicles for transportation in cities results in a growing demand for parking space and road network capacity. In many densely populated urban areas, however, the capacity of existing infrastructure is insufficient and extremely difficult to expand. Mobility-on-demand systems have been proposed as a remedy to the problem of limited parking space because they are able to satisfy the existing transportation demand with fewer shared vehicles and consequently require less parking space. Yet, the impact of large-scale vehicle sharing on traffic patterns is not well understood. In this work, we perform a simulation-based analysis of consequences of a hypothetical deployment of a large-scale station-based mobility-on-demand system in Prague and measure the traffic intensity generated by the system and its effects on the formation of congestion. We find that such a mobility-on-demand system would lead to significantly increased total driven distance and it would also increase levels of congestion due to extra trips without passengers. In fact, 38% kilometers traveled in such an MoD system would be driven empty.

Comment: accepted for ITSC 2017

Poro-Elastoplastic Modelling of Uplift Resistance of Shallowly-Buried Pipelines

Scipedia content — Wed, 03 Feb 2021 17:34:28 +0100

During operational cycles of heating and cooling of submarine pipelines, variations of temperature and internal pressure may induce excessive axial compressive force along the pipeline and lead to global buckling of the pipeline. Reliable design against upheaval buckling of a buried pipeline requires the uplift response to be reasonably predicted. Under wave loading, the effective stress of soil could be reduced significantly in the seabed under wave troughs. To investigate the effects of wave-induced pore-pressure on the soil resistance to an uplifted buried pipeline, a poro-elastoplastic model is proposed, which is capable of simulating the wave-induced pore-pressure response in a porous seabed and the development of plastic zones while uplifting a shallowly-buried pipeline. The uplift force on the buried pipeline under wave troughs can be generated by the pore-pressure nonuniformly distributed along the pipe periphery. Numerical results show that the value of uplift force generally increases linearly with the wave-induced mudline pressure under troughs. Parametric study indicates that the peak soil resistance (under wave troughs) decreases with increasing wave height and wave period, respectively. The ratio of peak soil resistance under wave action to that without waves is mainly dependent on the normalized wave-induced mudline pressure, but influenced slightly by the internal friction angle of soil.

Ontology for a voice transcription of OpenStreetMap data: the case of space apprehension by visually impaired persons

Scipedia content — Wed, 03 Feb 2021 17:31:37 +0100

In this paper, we present a vocal ontology of"br" OpenStreetMap data for the apprehension of space by visually"br" impaired people. Indeed, the platform based on produsage gives a"br" freedom to data producers to choose the descriptors of geocoded"br" locations. Unfortunately, this freedom, called also folksonomy leads"br" to complicate subsequent searches of data. We try to solve this issue"br" in a simple but usable method to extract data from OSM databases in"br" order to send them to visually impaired people using Text To Speech"br" technology. We focus on how to help people suffering from visual"br" disability to plan their itinerary, to comprehend a map by querying"br" computer and getting information about surrounding environment in"br" a mono-modal human-computer dialogue.

Document type: Conference object

A simple method to assess walkability around metro stations

Scipedia content — Wed, 03 Feb 2021 17:25:10 +0100

The ability to walk or ride a bike safely to and from metro stations is essential to the success of any metro service, especially for car users switching to the service. The main purpose of this study is to develop and apply a simple method to assess, compare, and rank walkability around different metro stations, with a priority order and specific recommendations for improvements. The proposed method depends on extracting different walkability variables in the catchment areas around metro stations. Three catchment areas around three proposed metro stations in the emerging city of Doha, Qatar were investigated using the proposed method to demonstrate its usefulness. The method was successful in comparing and ranking the different catchment areas, in addition to identifying priority areas for walkability enhancements in each area. This method is simple and can benefit professionals, practitioners, and policy makers to make swift decisions for future corrective measures, and can also be used to evaluate changes over time. 2018 Inderscience Enterprises Ltd. Scopu

VaseSketch: Automatic 3D representation of pottery from paper catalog drawings

Scipedia content — Wed, 03 Feb 2021 17:24:27 +0100

We describe an automated pipeline for digitization of catalog drawings of pottery types. This work is aimed at extracting a structured description of the main geometric features and a 3D representation of each class. The pipeline includes methods for understanding a 2D drawing and using it for constructing a 3D model of the pottery. These will be used to populate a reference database for classification of potsherds. Furthermore, we extend the pipeline with methods for breaking the 3D model to obtain synthetic sherds and methods for capturing images of these sherds in a way that matches the imaging methodology of archaeologists. These will serve to build a massive set of synthetic sherd images that will help train and test future automated classification systems.

Document type: Conference object

Detection and recognition of traffic signs inside the attentional visual field of drivers

Scipedia content — Wed, 03 Feb 2021 17:23:08 +0100

Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our technique detects and recognizes signs which are in the field of view of the driver and also provides indication when one or more signs have been missed by the driver.

Research on the Road Transport Risk of Domestic Hazardous Chemicals

Scipedia content — Wed, 03 Feb 2021 17:21:06 +0100

Contribution to partial discharge analysis in inverter-fed motor windings for automotive application

Scipedia content — Wed, 03 Feb 2021 17:17:55 +0100

International audience; The work presented here is part of a larger study concerning the analysis of electrical stress and degradation phenomena of electrical insulation of low voltage machines fed by Pulse Width Modulation (PWM) controlled inverter. The goal is to assess the risk of partial discharge (PD) in stator windings of rotating machines. In this objective, two complementary approaches are adopted: electrostatic simulations using Finite Element Method (FEM) in 2D approximation, and experimental measurements. The model seems to be a good tool allowing an approximation of PD occurrence in a given wire type. In the experimental part of this study, a simple and efficient method to detecting PD under PWM controlled voltage is presented.

Exploiting and Evaluating a Supervised, Multilanguage Keyphrase Extraction Pipeline for Under-Resourced Languages

Scipedia content — Wed, 03 Feb 2021 17:16:11 +0100

This paper evaluates different techniques for building a supervised, multilanguage keyphrase extraction pipeline for languages which lack a gold standard. Starting from an unsupervised English keyphrase extraction pipeline, we implement pipelines for Arabic, Italian, Portuguese, and Romanian, and we build test collections for languages which lack one. Then, we add a Machine Learning module trained on a well-known English language corpus and we evaluate the performance not only over English but on the other languages as well. Finally, we repeat the same evaluation after training the pipeline over an Arabic language corpus to check whether using a language-specific corpus brings a further improvement in performance. On the five languages we analyzed, results show an improvement in performance when using a machine learning algorithm, even if such algorithm is not trained and tested on the same language.

Factors influencing European passenger demand for air transport

Scipedia content — Wed, 03 Feb 2021 17:10:07 +0100

Passenger air travel demand is influenced by various factors and is crucial to manufacturers, airlines, airports and wider industry. In order to gain detailed insights into drivers of European air transport demand, five factors are analysed, both quantitatively and qualitatively. Focusing on the European air transport market, a detailed description of factors influencing air transport demand serves as input for a statistical analysis. Data from European countries on the gross domestic product per capita (GDP), urbanisation levels, the geographical location of a country, and the degree of education is used for the model. These explanatory variables are tested using a regression analysis in regard to their influence on the passengers’ demand for air transport. Results from the regression analysis reveal that the factors GDP, the geographical location of a country and the level of education are statistically significant, confirming GDP as a demand driver already examined within various studies that also include other factors as explanatory variables. Results also indicate the dynamics between the different factors, such as the positive relationship between income and level of education. Present studies are a good basis to show what drives demand, often focused at a global or country level. This analysis also confirms the essential determinants at a European level.

Vehicle rebalancing for Mobility-on-Demand systems with ride-sharing

Scipedia content — Wed, 03 Feb 2021 17:05:46 +0100

Recent developments in Mobility-on-Demand (MoD) systems have demonstrated the potential of road vehicles as an efficient mode of urban transportation Newly developed algorithms can compute vehicle routes in real-time for batches of requests and allow for multiple requests to share vehicles. These algorithms have primarily focused on optimally producing vehicle schedules to pick up and drop off requests. The redistribution of idle vehicles to areas of high demand, known as rebalancing, on the contrary has received little attention in the context of ride-sharing. In this paper, we present a method to rebalance idle vehicles in a ride-sharing enabled MoD fleet. This method consists of an algorithm to optimally partition the fleet operating area into rebalancing regions, an algorithm to determine a real-time demand estimate for every region using incoming requests, and an algorithm to optimize the assignment of idle vehicles to these rebalancing regions using an integer linear program. Evaluation with historical taxi data from Manhattan shows that we can service 99.8% of taxi requests in Manhattan using 3000 vehicles with an average waiting time of 57.4 seconds and an average in-car delay of 13.7 seconds. Moreover, we can achieve a higher service rate using 2000 vehicles than prior work achieved with 3000. Furthermore, with a fleet of 3000 vehicles, we reduce the average travel delay by 86%, the average waiting time by 37%, and the amount of ignored requests by 95% compared to earlier work at the expense of an increased distance travelled by the fleet.

Geotechnical Case History for Sinkhole Investigation and Stabilization Methods along a High Pressure Petroleum Pipeline

Scipedia content — Wed, 03 Feb 2021 17:00:54 +0100

Installation of underground pipelines through unpopulated land situated over pinnacled carbonate bedrock can lead to the development of sinkholes. The formation of sinkholes beneath buried pipelines has the potential of damaging the pipeline and more importantly causing hazardous environmental incidents. This paper presents a case history at a site where significant sinkholes developed within and adjacent to a 400 foot (112 meters) long section of high pressure petroleum pipeline right-of-way that crosses under a local creek in Plymouth Meeting, Pennsylvania. Various geophysical investigation techniques consisting of microgravity, multi-channel analysis of surface waves (MASW), and two dimensional electrical resistivity testing were performed in addition to confirmatory testing borings to effectively evaluate the subsurface conditions at the site. Three options were considered as a solution to the active sinkholes present within the pipeline rightof-way. These options include: 1) subsurface grouting within the right-of-way 2) structurally supporting the pipeline on a deep foundation system or 3) relocating the pipeline to a less sinkhole prone portion of an adjacent property. Following the investigation process, relocating the pipeline in conjunction with pre-installation ground improvements via subsurface grouting represented the most cost-effective, lowest risk solution at the site. Introduction In January 2009 a sinkhole developed below an active petroleum pipeline that crossed under a local creek in Plymouth Meeting, Pennsylvania. Upon initial discovery, it was reported that the sinkhole measured approximately 9 feet (3 meters) in diameter by 9 feet (3 meters) in depth causing the pipeline to be unsupported across a portion of the open void. Representatives of the pipeline company filled in the sinkhole with various materials that ranged from tree stumps to geotextile filter fabric and well-graded aggregates as a temporary solution to the problem. Following the temporary backfill measures, the owner recognized the severity of the problem and the need for the expertise of a geotechnical engineering firm. Initially, a feasibility study was conducted to determine the most cost-effective and best long term solution at the site. The options considered include: 1) subsurface grouting within the right-of-way 2) structurally supporting the pipeline on a deep foundation system or 3) relocating the pipeline to a less sinkhole prone portion of an adjacent property. The first step in the study was to perform a site reconnaissance and a stereographic aerial photograph review. Due to the site being primarily wooded, inconclusive results were found from the aerial photograph review. During the site reconnaissance, the streambed was dry on each side of the pipeline crossing. The stream bed remained dry for approximately 500 to 600 yards (457 to 549 meters) upstream of the sinkhole at the pipeline crossing. Further inspection revealed a large sinkhole had created a disappearing stream condition upstream of the pipeline crossing. Photograph 1 shows the large sinkhole upstream of the pipeline crossing. The overall topography within the pipeline right-of-way slopes gently to moderately downwards toward the creek and sinkhole locations. Photograph 2 shows the area of study within the pipeline right-of-way. The overall topography within the pipeline right-of-way slopes gently to moderately downwards toward the creek and sinkhole locations. Photograph 2 shows the area of study within the pipeline right-of-way. Project Description and Background During low flow conditions, the creek water disappears into the upstream sinkhole leaving the downstream side dry. During periods of steady rainfall, storm water

Graph Constraints in Urban Computing: Dealing with conditions in processing urban data

Scipedia content — Wed, 03 Feb 2021 16:59:52 +0100

International audience; Smart Cities is a worldwide initiative leading to better exploit the resources in a city in order to offer higher level services to people. In this context, urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, traffic devices, vehicles, buildings, and humans, to tackle the major issues that cities face, e.g. air pollution , increased energy consumption and traffic congestion. The majority of these information can be represented as graphs, such as the transportation network, in which places (nodes) are connected by some form of public transportation (edges). A vision of the " city of the future " , or even the city of the present, rests on the integration of science and technology through information systems. This vision requires a rethinking of the relationships between technology, government, city managers, business, academia and the research community. This position paper presents our views towards developing techniques for querying and evolving graph-modeled datasets based on user-defined constraints. Our focus is to show how these techniques can be applied to effectively retrieve urban data and have automated mechanisms that guarantee data consistency.

Analyzing the layout of China’s strategic petroleum reserve base

Scipedia content — Wed, 03 Feb 2021 16:56:21 +0100

With the development of China’s economy, its dependence on foreign oil increases every year. Therefore, oil reserves play a vital role in ensuring China’s energy security. The selection of a base site for the construction of strategic oil reserves is a priority. This study analyzes the status quo as well as future development trends for oil processing conditions, pipeline transportation conditions, consumption and production in the base radiation area, crude oil loading and unloading capacity of the port, reserve modes, and other factors. Preliminary planning of the spatial layout of the petroleum strategic reserve base is also detailed in this study. Strategic oil reserve bases can be positioned at the Pearl River Delta, the crude oil pipelines of Central and Southwest China and the large refineries and locations near the crude oil port terminals. Meanwhile, ground and underground reserve modes should be combined.

Driver Distraction: A Naturalistic Observation of Secondary Behaviors With the Use of Driver Assistance Systems

Scipedia content — Wed, 03 Feb 2021 16:56:08 +0100

This report describes the naturalistic observation of secondary behaviors performed by 66 drivers who took part in the Automotive Collision Avoidance System Field Operational Test (ACAS FOT). The ACAS FOT included two driver assistance systems, adaptive cruise control (ACC) and forward collision warning (FCW). Each driver participated in both baseline (no driver assistance systems for one week) and treatment conditions (both ACC and FCW available for 3 weeks). The method employed was to sub-sample video data, and code drivers’ secondary behaviors using 4 s video clips of the driver, collected every 5 minutes. Eight-hundred and ninety video clips were reviewed and coded while participants drove manually, with conventional cruise control, ACC, and FCW. The results show that drivers who took part in the field test were no more likely to engage in secondary behaviors when driving with ACC and FCW in comparison to manual control. When the driver assistance systems became available to the participants, there was an increase in the number of conversations drivers had with passengers, probably related to the driver explaining the novel ACAS system to passengers. The results have important implications in that, at least for the duration of exposure examined, they counter the concern often raised that driver assistance systems will promote driver distraction, lapses in attention or modification in perceived risk.

CLIMBING ROBOTS FOR NDT APPLICATIONS

Scipedia content — Wed, 03 Feb 2021 16:48:22 +0100

variety of automated solutions for non-destructive testing have been developed to facilitate in-situ sensing for inspection requirements to ensure safety and effective operation in a variety of hazardous application scenarios. The paper focuses on climbing robot technologies which have been developed to monitor the condition of assets such as concrete pillars, highway bridges, tunnels, wind turbine blades and towers, hull ships, pipelines, nuclear installations, etc. A review of the robot technologies is presented together with a number of climbing robots being developed via magnetic and vacuum adhesion.

Scipedia: Documents published in 2017

External costs estimation in a cost-benefit analysis: The new Formia-Gaeta tourist railway line in Italy

Hierarchical Decomposition Approach for Detailed Scheduling of Pipeline Systems with Branches

Stakeholder impact on the software architecture of intelligent transport systems implementations

The effect of see-through truck on driver monitoring patterns and responses to critical events in truck platooning

Numerical Modelling of Interference from AC Power Lines on Buried Metallic Pipelines in Presence of Mitigation Wires

Driving into the memory wall

Evaluation of safety indicators for truck platooning

Multi-agent system for managing energy storage using electric vehicles

Demand Response and Energy Portfolio Optimization for Smart Grid using Machine Learning and Cooperative Game Theory

Key performance indicators for assessing the impacts of automation in road transportation: Results of the Trilateral key performance indicator survey

Research and Application of Public Traffic Intelligent Dispatching Based on Dynamic Programming Algorithm

Enabling Driver Feet Gestures Using Capacitive Proximity Sensing

Fault detection and isolation in flat navigation canals

Sustainable Decision-Making using the COMET Method: An Empirical Study of the Ammonium Nitrate Transport Management

Impact analysis of freight vehicle access restriction (A case study of Jakarta Intra Urban Toll way)

An Alternative Time Metric to Modified Tau for Unmanned Aircraft System Detect And Avoid

A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing

Comparing MapReduce and Pipeline implementations for Counting Triangles

Evolutionary computation at work for the optimization of link state routing protocols

Detection of non-recurrent road traffic events based on clustering indicators

A real-time autonomous highway accident detection model based on big data processing and computational intelligence

The effect of wind turbines alongside motorways on drivers’ behaviour

Learning Air Traffic Controller Workload from Past Sector Operations

Information Modeling for Thermal Fatigue Evaluation of Power Plant Pipelines

Bayesian Test Design for Reliability Assessments of Safety-Relevant Environment Sensors Considering Dependent Failures

One step at a time: Optimizing SDN upgrades in ISP networks

Openstreetmap A Servizio Delle Emergenze

The Research of Optimal Length of Left Turn with U-turn at Intersection Based on Statistical and Simulation Analysis

Identifying barriers in shared mobility implementation, a review

Developments in Cooperative Intelligent Vehicle-Highway Systems and Human Factors Implications

Osm Seen From A Gis Researcher: Experiences & Perspectives

Combined Solar Charging Stations and Energy Storage Units Allocation for Electric Vehicles by Considering Uncertainties

Simulating impacts of regulatory policies on urban freight: application to the catering setting

Towards a sustainable hydrogen economy: Optimisation-based framework for hydrogen infrastructure development

Enhancing the Financial Feasibility of PPP Projects with Hybrid Funding

PV-Alert: A fog-based architecture for safeguarding vulnerable road users

Integrated One-Dimensional Modeling of Asphaltene Deposition in Wellbores/Pipelines

Driver Behaviour Studies in the Motorway Operations Platform Grant

An Efficient Approximation Algorithm for Traffic Engineering in Software Defined Networks

Assessment System of Community Road based on the Spatial Dimension

Enhance the sustainability of private land transport system at Ayer Keroh, Melaka

Examining the relationships between individual’s time use and activity participations with their health indicators

Encouraging Environmentally Friendly Driving Through Driver Assistance: The eCo Move Project

Erosion regularities of gas pipelines based on the gas-solid two-way coupling method

One-to-One Matching of RTT and Path Changes

HyperLoom

Stress analysis of vibrating pipelines

Hybrid modeling for vineyard harvesting operations

Electric vehicles energy management using direct torque control — space vector pulse width modulation combined to polynomial controllers

Characterizing Driving Context from Driver Behavior

Jamming and Spoofing Protection for ADS-B Mode S Receiver Through Array Signal Processing

Development and evaluation of two learning-based personalized driver models for car-following behaviors

A Configurable Framework for Hough-Transform-Based Embedded Object Recognition Systems

Optimized and enhanced grid architecture for electric vehicles in Europe

No need to learn from each other?: Potentials of Knowledge Modeling in Autonomous Vehicle Systems Engineering

THE BARRIERS IN THE IMPLEMENTATION PROCESS AND THE OPERATION OF INNOVATIVE URBAN TRANSPORT: THE CASE OF BRT JAKARTA

A Programmable SDN+NFV-based Architecture for UAV Telemetry Monitoring

Learning Less is More - 6D Camera Localization via 3D Surface Regression

Study on the propagation and dissipation of inland ship congestion under different control strategies

How Close Can I Be? - A Comprehensive Analysis of Cellular Interference on ATC Radar

Time mobility

A Standard Mission Profile for Hybrid-Electric Regional Aircraft based on Web Flight Data

A Survey on Urban Traffic Optimisation for Sustainable and Resilient Transportation Network

Low-Latency Routing on Mesh-Like Backbones

A new trans-Atlantic route structure for strategic flight planning over the NAT airspace

Technological and Operational Scenarios on Aircraft Fleet-Level towards ATAG and IATA 2050 Emission Targets

Behavioural Change Support Intelligent Transportation Applications

What is a Learning Town? Reflections on the Experience at Wirksworth

Open source tools for locomotion and apprehension of space by visually impaired persons: some propositions to build a prototype based on Arduino, speech recognition and OpenStreetMap

An offshore energy simulation through flow networks: CEL within the MSP Challenge 2050 simulation game platform

Analysis on logistic company action toward the access restriction policy on freight vehicle

Alternative Trajectory Options for Delay Reduction in Demand and Capacity Balancing

Including linear holding in air traffic flow management for flexible delay handling

Proposing bat inspired heuristic algorithm for the optimization of GMPLS networks

On Canonical Polyadic Decomposition of Non-Linear Gaussian Likelihood Functions

Kafka interfaces for composable streaming genomics pipelines

Fault injection method for safety and controllability evaluation of automated driving

Analyzing and managing the slot occupancy of car parking by exploiting vision-based urban surveillance networks

Health impact modelling of different travel patterns on physical activity, air pollution and road injuries for São Paulo, Brazil

Encouraging Environmentally Friendly Driving Through Driver Assistance: The eCo Move Project