Abstract

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

Abstract

TRA 2018, 7th Transport Research Arena, Vienne, AUTRICHE, 16-/04/2018 - 19/04/2018; Especially in inter-country areas, Crisis Management (CM) faces several challenges. Thorough preparation and anticipation are crucial organizational tools to address those challenges and enable proper reaction to crises. CM requires the joint effort of various stakeholders from different countries: public authorities, private companies, Non-Governmental Organizations (NGOs), etc. need to collaborate under specific, locally different regulations. The present paper includes a brief introduction to the state of the art of CM of international railways with special regard to the topics partnerships, leadership & communication as well as training. As part of a research project, a survey with international crisis management experts was conducted. Based on the survey results, a handbook containing transnational recommendations regarding the involved stakeholders and their responsibilities is developed. Of course, existing CM concepts of relevant organizations are taken into consideration for the development. The handbook was discussed with end-users in the course of a project workshop. In addition, when the crisis management is required, the response is coordinated within the framework of the National Crisis Management System (NCMS). The cooperation between these NCMSs leads to the concept of System-of-Systems (SoS). Based on Supervision Control Theory (SCT), we propose a formal model built from decomposition of NCMSs using a multi-model approach. The resulted framework offers a global view of the SoS and resolves problems of system's dependence and of operating mode management. The proposed model is designed by using the High Level Petri Nets (HLPNs) formalism and is illustrated with a crisis of a railway system. The main result of this paper is the comprehensive knowledge of current crisis management strategies in the context of cross-border incidents. Weaknesses in the existing system are identified and two approaches that seek to enhance CM are introduced.

Abstract

hEART 2019, 8th Symposium of the European Association for Research in Transportation, Budapest, HONGRIE, 04-/09/2019 - 06/09/2019; In recent years, intelligent transportation systems made it possible for operators to adapt in real-time the transportation supply to travel demand via new mobility services. Among these services, ride-sharing is becoming popular. The dynamic ride-sharing problem involves two sub-problems: (1) How to serve the upcoming trips (Optimal fleet management) and (2) How to accurately predict the travel times to determine vehicles availability and pick up/drop off times. In this paper, we express the optimal fleet management problem as a constrained multi objective integer linear programming. Our aim is to find the global optimal solution for the ride-sharing problem without uncertainty in demand to have a vision of these services performance in optimal situation. Then we compare the results and experiments with the exact optimal condition. We have designed an algorithm to find the exact solution for matching problem based on the branch and bound algorithm. To solve the second sub-problem, we define two different models to assess the impact of traffic conditions on the dynamic ride-sharing system performance for large-scale problems.

Abstract

XVI DECGE 2018 Proceedings of the 16th Danube European Conference on Geotechnical Engineering, SKOPJE, MACÉDOINE DU NORD, 07-/06/2018 - 09/06/2018; To study the development of liquefaction in ore cargo during maritime transportation, a new Rolling Test device has been designed to support similar stresses than those observed in a vessel. It can be used in an 80×g macrogravity field in the 5.5m radius IFSTTAR geo-centrifuge. Its main characteristics and benchmark test results are presented.

Abstract

Increasing mobility and congestion results in an increase in travel time variability and in a decrease in reliability. Reliability becomes an important performance measure for transportation facilities. A variety of performance measures have been proposed to quantify it. Many of these indicators are based on percentiles of travel time. The knowledge of the distribution of travel time is needed to properly estimate these values. Congestion distorts the distribution and particular statistical distributions are needed. Different distributions have been proposed in the literature. In a previous paper, we presented a comparison of six statistical distributions used to model travel time. These six distributions are the Lognormal, Gamma, Burr (extended by Singh-Maddala), Weibull, a mixture of two Normal distributions and a mixture of two Gamma distributions. In this paper a probabilistic modeling of travel time which takes into account the levels-of-service is given. Levels of service are identified, then travel time distributions are modeled by level of service. This results in a very good fit between the empirical and modeled distributions Moreover, the adjustment was improved, thanks to the calibration of “Bureau of Public Roads” functions, linking the travel time to the traffic flow by level of service. The superiority of the Singh-Maddala distribution appears in many cases. This has been validated, thanks to travel time data from the same site at another period. However the parameters of the distributions vary from one year to another, due to changes in infrastructure. The transferability of the approach, not performed, will be based on travel time data on another site. Document type: Conference object

Abstract

Driving simulators have been becoming little by little a suitable tool oriented to improve the knowledge about the domain of driving research. The investigations that can be conducted with this type of tool concern the driver’s behaviour, the design/control of vehicles, testing assistance systems for driving and the roadway infrastructure’s impact. The benefits of simulation studies are many: lack of any real risk to users, reproducible situations, time savings and reduced testing costs. In addition, their flexibility allows to test situations that do not exist in reality or at least they rarely and randomly exist. The topic of the present work concerns the development of a brand new dynamic model for an existing car simulator owned by LEPSIS laboratory (Laboratoire d’Expliotation, Perception, Simulateurs et Silulations – Laboratory for Road Operations, Perception, Simulators and Simulations) belonging to COSYS (COmposants et SYStems), which is a department of IFSTTAR institute (Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux – French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks) site. Once uses and advantages of driving simulators are listed and described, imperfections and limitations of the existing driving vehicle model belonging to the two Degrees of Freedom (DoF) driving simulator of the laboratory are highlighted. Subsequently, structure of the brand new vehicle model, designed by means of Matlab Simulink software, are illustrated through the theoretical framework. Since the vehicle model must refer to a real one, an instrumented Peugeot 406 has been chosen because all its technical features are provided and inserted both on the present model and Prosper/Callas 4.9 by OKTAL software to create a highly sophisticated and accurate virtual version of the commercial car. The validation of this new vehicle model is performed, where the results returned by several different driving scenarios are compared with the ones provided by Prosper software. All the scenarios are simulated with both existing and new vehicle model uploaded in the driving simulator, and the outputs are subsequently compared with the ones returned by Prosper in order to demonstrate the improvements done. Finally, being the number of outputs provided by the new model definitively higher with respect to previous one, additional validations concerning the further results are accomplished.

Abstract

We conduct a Global Sensitivity Analysis (GSA) of urban-scale network performances to parameters representing a wide range of realistic dynamic loadings, decomposed in a choice of OD matrix, routing alternatives, and paths flow distribution. A special attention is given to the route alternatives generation, where overlapping metrics and selection methods are introduced to reproduce a wide variety of paths sets configuration. Paths flow distributions are calculated based on different equilibrium criteria. Several sets of simulations are conducted and analyzed graphically and then with a variance-based GSA method so as to get insights on how much and in which conditions each network loading parameter influences network performances by itself or by interaction. Results notably reveal that the demand level is the most decisive parameter since low values simply lead to free-flow conditions with no influence of the other parameters, whereas higher values lead to a wide diversity of network states going from close to capacity but stable to gridlocked. While a nonnegligible amount of this disparity is explained by the demand pattern parameter, the number of paths per OD, their overlapping, and the equilibrium criterion of the paths flow distribution are still influential enough to maintain the network close to its optimal capacity or to prevent the network from fast collapse (gridlock). The highlighted connection between spatial and temporal heterogeneities of the network states explains the gridlocking phenomena. These extracted insights are very encouraging for operational implementations. Document type: Article

Abstract

Reliable and unceasing exploitation of power electronic converters plays a major part in every application. This PhD thesis comes up with new opened-up reliability assessment frameworks and demonstrates the feasibility of using multistate degraded system analysis and interval analysis as well for attaining much more accuracy in reliability evaluation. Considering self- and coupling degradation effects of the items and assessing reliability in the system level are important issues which are still lacking in the previous studies and the present thesis has made an effort to overcome these problems. The thesis tries to launch two distinct reliability assessment frameworks, namely interval reliability and Multistate degraded system reliability.Interval reliability is capable of introducing an interval useful lifetime for DC-DC power electronic converters in which the self and coupling degradations effects of items have been taken into account. Fundamentally, it is based on the conventional physics of failure reliability assessment. Based on this method, instead of obtaining an inaccurate reliability value, one can attain an interval for the reliability of a global system whose useful lifetime undoubtedly lays between the boundaries. This method is able to consider degradation dependencies and assess multi-component system level reliability but not redundant system. An attempt was made to enhance the conventional reliability framework to reach a systematic approach capable of estimating a reliability assessment considering self and mutual degradation effects and being able to evaluate system-level reliability including redundant system. Multistate degraded system reliability analysis is capable of estimating system-level reliability, while mission profile and physics of failure of the system’s items are taken into account. In addition, the self and mutual degradation effects of items on the operation of the global system have been considered. The multi-state degraded system reliability model exposed to multiple failure processes has been generalized. The operating condition of the global system is defined by a finite number of states. Not only can the proposed framework be employed in determining the reliability of the degraded systems in terms of multi-state functions, but also it can obtain the states of the systems by estimating the system state probabilities.As an application, a DC-DC power electronic system containing three critical items has been studied. In this case study, two power semiconductors, namely IGBT and diode, and a power capacitor have been considered as three degradation processes and their aging effects on the useful lifetime estimation of the power electronic system have been discussed. For having a sense about newly proposed reliability frameworks, a 3000W and 200/400 V conventional DC-DC converter for electric vehicle application exposed to WLTP driving cycle is considered.; La fiabilité et la sureté de fonctionnement de l'électronique de puissance jouent un rôle majeur aujourd'hui dans l'industrie. Cette thèse propose un nouveau cadre d'étude de la fiabilité à partir de deux méthodes afin d'améliorer la précision des études de fiabilité : une analyse utilisant la méthode des système dégradés multi état, et une analyse par intervalles. La considération des effets de dégradation propres et couplés de chaque composant est également une problématique qu'il reste aujourd'hui à étudier et qui est traitée dans ce travail.L'étude de la fiabilité par intervalles permet d'estimer des intervalles de durée de vie des convertisseurs DC/DC en prenant en compte les dégradations propres et mutuelles des composants. Fondamentalement, cette méthode est basée sur la compréhension des phénomènes physiques. A partir de cette méthode, on peut obtenir un intervalle pour la durée de vie d'un système complet. Cette méthode n'est toutefois pas adaptée aux systèmes redondants.De son côté, la fiabilité des systèmes dégradés multi-états est capable de proposer une étude au niveau système en prenant en compte le profil de mission et la physique des dégradations.Cette méthode a été généralisée dans cette thèse au procédés subissant de multiples dégradations. L'exemple d'un convertisseur DC/DC conprenant trois composants critiques a été étudié comme cas d'application. Deux composants semiconducteurs, diode et IGBT, et un condensateur sont considérés comme trois process de dégradation et l'effet de leur vieillissement sur la durée de vie du convertisseur est discutée. Le convertisseur étudié a pour puissance 3 kW (200/400V) et est dédié aux applications de type véhicule électrique. Il subit un profil de mission typique automobile (cycle WLTP).