Laboratoire de Génie Informatique et d’Automatique de l’Artois


Ph.D. student
(Left the LGI2A in 2014)
Member of the research axes:
Methods using belief functions to manage imperfect information concerning events on the road in VANETs
Transportation Research Part C: Emerging Technologies, pp 299–320, Vol. 67, juin 2016
Methods handling accident and traffic jam information with belief functions in VANETs
3rd International Conference on Belief Functions, BELIEF 2014, pp 124-133, Oxford, United Kingdom, F. Cuzzolin (Ed.), septembre 2014
A high-level application using belief functions for exchanging and managing uncertain events on the road in vehicular ad-hoc networks
Annals of telecommunications: special issue on belief functions and uncertainty management in networks and telecommunication, pp 185-199, Vol. 69, No. 3-4, , avril 2014
International conference with review committee
Exchanging dynamic and imprecise information in V2V networks with belief functions
16th Int. IEEE Conf. on Intelligent Transport Systems, 6-9 october, ITSC 2013, pp 967-972, The Hague, The Netherlands, janvier 2013
Un processus V2V d’échanges et de gestion d’informations imparfaites basé sur des fonctions de croyance
21e Rencontres Francophones sur la Logique Floue et ses Applications (LFA 2012), pp 71-78, Compiègne, France, novembre 2012
International conference with review committee
Towards a robust exchange of imperfect information in inter-vehicle ad-hoc networks using belief functions
IEEE Intelligent Vehicles Symposium, pp 436-441, Baden-Baden, Germany, juin 2011

Author of the Ph.D. thesis "Methods using belief functions to manage imperfect information in vehicular networks"

2010 - 2014

The popularization of vehicles has created safety and environmental problems. Projects have been launched worldwide to improve road safety, reduce traffic congestion and bring more comfort to drivers. The vehicle network environment is dynamic and complex, sources are often heterogeneous, and therefore the exchanged information may be imperfect. The theory of belief functions offers flexibility in uncertainty modeling and provides rich tools for managing different types of imperfection. It is used to represent uncertainty, manage and fuse the various acquired information. We focus on the management of imperfect information exchanged between vehicles concerning events on the road. The carried work distinguishes local events and spatial events, which do not have the same characteristics. In an environment without infrastructure where each vehicle is a fusion center and creates its own vision, the goal is to provide to each driver the synthesis of the situation on the road as close as possible to the reality. Different models using belief functions are proposed. Different strategies are considered: discount or reinforce towards the absence of the event to take into account messages ageing, keep the original messages or just the fusion result in vehicle database, consider the world update, manage the spatiality of traffic jam events by taking into account neighborhood. Perspectives remain numerous; some are developed in the manuscript as the generalization of proposed methods to all spatial events such as fog blankets.

PlaiiMob (CISIT)

2007 - 2013

Plate-forme de simulation dédiée aux services de MOBilité

Summary :

The objective of this project is to illustrate how partial information can be exchanged in the context of inter-vehicle communication, for example to warn the driver of a potentially dangerous event (accident, obstacles on the road, braking, ...) or to assist him/her (find a free parking space, avoid traffic jams, be informed in real time of traffic conditions).