Smart distance keeping: modeling and perspectives for embedded diagnosis

Hassan Shraïm (1) , Othman Nasri (2) , Philippe Dague (3, 4) , Olivier Héron (5) , Mickael Cartron (5)

1 Sherpa Engineering
2 ENISo - National Engineering School of Sousse / Ecole Nationale d'Ingénieurs de Sousse
3 LRI - Laboratoire de Recherche en Informatique
4 LEO - Distributed and heterogeneous data and knowledge
5 LIST (CEA) - Laboratoire d'Intégration des Systèmes et des Technologies

This paper presents a detailed description of an advanced Adaptive Cruise Control (ACC) system implemented on a Renault-Volvo Trucks vehicle. One of the main differences between this new system, which is called the Smart Distance Keeping (SDK), and the classical ACC is the choice of the safe distance. This later is the distance between the vehicle (with the ACC or the SDK system) and the front obstacle (which may be a vehicle). It is supposed fix in the case of the ACC, while variable in the case of the SDK. The variation of this distance (in the case of SDK) depends essentially on the relative velocity between the vehicle and the front obstacle. The choice of this distance influences the velocity regulation. The main contribution of this work is on the SDK system architecture, the design of its environment model, and the proposition of a detection and isolation strategy for some of the possible faults that may be produced on the system.

Domaines: Intelligence artificielle [cs.AI]; Systèmes embarqués; Performance et fiabilité [cs.PF]; Automatique

Hassan Shraïm, Othman Nasri, Philippe Dague, Olivier Héron, Mickael Cartron. Smart distance keeping: modeling and perspectives for embedded diagnosis. 1rst International Conference on Intelligent Systems, Modelling and Simulation ISMS'10, Jan 2010, Liverpool, United Kingdom. ⟨inria-00540819⟩