Positionnement dans le cursus
Semestre 5
Intersemestre
Semestre 6
 
 
 
Semestre 7
 
Intersemestre
Semestre 9
 
 
Intersemestre

Course unit

Connected intelligent transport systems

Last updated: 22/02/2024

Edit

Course Director(s):

FEILLET Dominique BALBO Flavien

General Description:

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.

Key words:

Collaborative models Geographic information system Mobile network Operational research

Number of teaching hours

40

Fields of study

Computer Science, Information Systems

Teaching language

English

Intended learning outcomes

On completion of the unit, the student will be capable of: Classification level Priority
Understand the issues related to the development of communication and vehicle range 1. Knowledge Essential
Communicate in a mobile environment 3. Apply Essential
Manipulating a geographic information system 3. Apply Useful
Address a problem of transport network design or management through operational research techniques 3. Apply Useful

Learning assessment methods

Percentage ratio of individual assessment Percentage ratio of group assessment
Written exam: 0 % Project submission: 100 %
Individual oral exam: 0 % Group presentation: 0 %
Individual presentation: 0 % Group practical exercise: 0 %
Individual practical exercise: 0 % Group report: 0 %
Individual report: 0 %
Other(s): 0 %

Programme and content

Type of teaching activity Content, sequencing and 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.