Abstract

Carsharing continues to grow worldwide as a powerful strategy to provide an alternative to solo driving. The viability of electric vehicles, or EVs, has been exam-ined in various carsharing business models. Moreover, new technologies have given rise to electromobility, or e-mobility, systems. This paper discusses the evolution of e-mobility in carsharing business models and the challenges and opportunities that EVs present to carsharing operators around the world. Operators are now anticipating in-creased EV proliferation into vehicle fleets over the next 5-10 years as technology, infrastructure, and public policy shift toward support of e-mobility systems. Thus, re-search is still needed to quantify impacts of EVs in changing travel behavior toward more sustainable transport.

Abstract

This thesis focuses on the optimal design of one-way station-based carsharing systems. We consider the system design through two structural aspects: the optimal system dimensioning (number of parking places, vehicles, battery capacities, etc.) and the identification of appropriate stations’ locations. Although the addressed problems do not directly concern the system management, some relevant aspects (like vehicle relocation operations) are nonetheless part of the models. The modelling approach uses graph theory to represent the system dynamics over time and various optimization models (ILPs and MILPs) are proposed. The objective is to deduce an optimal shape of the whole system (number of vehicles, parking places, jockeys, stations’ locations, etc.) allowing to capture the maximum number of estimated time-dependent requests. Electric vehicles and power supply are also included in an enhanced model version and context related constraints ensure the integrity of the whole model. The optimization allows to study the impact of different power supply technologies and settle the minimal autonomy a shared vehicle necessitate in this environment. Models are applied to realistic case studies, using both random generated data and real estimated outputs of simulation tools. Strategies including vehicle relocation operations managed by jockeys (employees of the carsharing operator) are considered. We propose some graph simplifications reducing the problem size and leading to greatly improve solver capabilities as well as computation times. A greedy heuristic helping to quickly find feasible solutions and initialize the solver is also proposed and illustrated.; Cette thèse s'intéresse à la conception optimale d'un système d'autopartage de type one-way avec stations. Les problèmes abordés traitent de deux aspects structurels importants : le dimensionnement optimal du système (nombre de places de parking, de véhicules, de relocalisation de véhicules, etc.) et la localisation adéquate des stations. Bien que le management ou pilotage en temps réel du service ne soit pas l'objet de cette étude, certains aspects pertinents (relocalisation de véhicules, nombre de jockeys) ont toutefois été intégrés aux modèles. L'approche mathématique utilise des objets de la théorie des graphes pour représenter les systèmes dans le temps et les problèmes sont résolus grâce à la programmation linéaire en nombre entiers. L'objectif est d'identifier la structure du service permettant de capturer le plus de demandes possibles. L'introduction de véhicules électriques et de la puissance de charge en station sont étudiés dans un modèle dédié. Les expérimentations s'appuient sur des données réalistes, générées aléatoirement. Nous nous intéressons particulièrement aux pistes d'amélioration des temps de calculs et de réduction des graphes. Une heuristique gloutonne permettant d'identifier rapidement une solution réalisable est en particulier proposée. Enfin, une étude de dimensionnement des batteries confirme que des capacités deux fois inférieures à celles actuellement sur le marché sont viable dans le contexte urbain actuel.

Abstract

carsharing is developing rapidly worldwide, carsharing demand estimation becomes a more and more important issue, especially for an area that just introduces this service. Station-based one-way carsharing, as a new carsharing type, recently developed rapidly in China. Both policy-maker and operator want to know how the demand changes with increasing supply. To enrich understanding of these problems, this paper aims to make use of the muti-agent simulation tool (MATSim) to model and simulate one-way carsharing. The largest carsharing project in Shanghai, Evcard, is explicitly analyzed. Specifically, it intends to integrate the mobile phone GSM (Global System for Mobile Communications) data, point of interest data, network data and travel survey data to build a base simulation scenario with about 160,000 agents in the Jiading district, Shanghai. More data, for example the empirical data of operator, are used to calibrate the model. Some special functions, for example, the carsharing vehicles in simulation are pure battery electric vehicles, have been integrated into MATSim. Some preliminary results are presented and validated.