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Unité pédagogique

Connected intelligent transport systems

Derniere édition le: 22/02/2024

Modifier

Responsable:

FEILLET Dominique BALBO Flavien

Description générale :

The Connected Intelligent Transport System (ITS) module focuses on the development of informatics systems for the transportation of people and goods, with new generation of vehicles that are even more connected and autonomous. At the end of this course, students will have the technological skills to understand the issues and benefits of the use of modern information technologies and optimization algorithms in the transportation domain. They will manipulate a simulation system and develop optimization algorithms for centralized and decentralized transportation systems. The platform Territoire : (http://territoire.emse.fr/ ) will be used as a support for practical sessions.

Mots-clés:

Collaborative models Geographic information system Mobile network Operational research

Nombre d’heures à l’emploi du temps:

40

Domaine(s) ou champs disciplinaires:

Informatique, Systèmes d'information

Langue d’enseignement:

Anglais

Objectifs d’apprentissage:

A la fin de l’unité pédagogique, l’élève sera capable de : Niveau de taxonomie Priorité
Comprendre les enjeux liés au développement de la communication et de l’autonomie des véhicules 1. Connaître Essentiel
Communiquer en environnement mobile 3. Appliquer Important
Manipuler un système d’information géographique 3. Appliquer Utile
Aborder un problème de conception ou de pilotage de réseau de transport par des techniques de recherche opérationnelle 3. Appliquer Utile

Modalités d’évaluation des apprentissages:

Part de l'évaluation individuelle Part de l'évaluation collective
Examen sur table : 0 % Livrable(s) de projet : 100 %
Examen oral individuel : 0 % Exposé collectif : 0 %
Exposé individuel : 0 % Exercice pratique collectif : 0 %
Exercice pratique individuel : 0 % Rapport collectif : 0 %
Rapport individuel : 0 %
Autre(s) : 0 %

Programme et contenus:

Type d’activité pédagogique : Contenu, séquencement et organisation
Course

This module begins with a course about the architectural issues of the design of connected transportation systems. Centralized and distributed solutions are discussed as well as the constraints related to the multimodality, intermodality and dynamic dimensions of transportation networks (3h).

The second course presents the specificities of computer networks architectures and routing protocols for transportation applications (3h).

The third course is related to traffic management; the backgrounds of traffic modeling and traffic regulation are presented (3h).

The fourth course discusses the environment dimension i.e. the transportation network environment representation and the environmentally friendly traffic concepts 3h

Course

The module is continued with four 3-hour sessions about the modelling and the solution of transportation problems. Transportation of goods and people will be considered.  A special attention will be paid to the class of so-called “vehicle routing problems”, where a fleet of vehicles has to delivers goods (or transport users) to a set of destinations. Others categories of problems met in the design or the planning of transportation systems will also be covered (location problems, inventory routing problems, production routing problems, hub location problems…).

Practical courses

16 hours of practical sessions will conclude the module. The use-case will be the management of a fleet of taxis in an urban area. Two modes will be considered for the system. In a decentralized system, taxis communicate in order to coordinate their decision to optimize the number of satisfied traveler. In a centralized system, a central entity has access to all taxi locations and traveler requests, and takes global decisions for the assignment of taxis to requests. In both cases, dedicated simulation and optimization algorithms will be implemented. These developments will be integrated into an existing software platform and do not necessitate more than basic skills in programming. Numerical experiments on simulated data will permit to eventually highlight the pros and cons of each system.