Nowadays, more and more driving assistances are available to help the driver and to improve the vehicle handling. With increasing sensing capacities, it also becomes possible to have a local view of the vehicle surrounding. Hence, the next steps are to provide the driving assistances a supervisor that schedules all the possible actions and plane trajectories. In this article, we propose a decision method that fits the driver decision and action schemes. The system is at three levels, for action, decision and long range planning. the article is focused on the second layer and the interaction with other layer. The second layer algorithm, based on risk assumption, evaluates, in the vehicle vicinity, the risk related to each detected object. It then computes possible actions for lower level layer. The developed method is constrained by the future implementation on a vehicle : low computation time available and small memory size.
[1]
John A. Michon,et al.
A critical view of driver behavior models: What do we know
,
1985
.
[2]
Michel Parent.
Advanced Urban Transport: Automation Is on the Way
,
2007,
IEEE Intelligent Systems.
[3]
John C Hayward,et al.
NEAR-MISS DETERMINATION THROUGH USE OF A SCALE OF DANGER
,
1972
.
[4]
C A Hobbs,et al.
INJURY PROBABILITY FOR CAR OCCUPANTS IN FRONTAL AND SIDE IMPACTS
,
1984
.
[5]
Nadine Le Fort-Piat,et al.
Safe Task Planning Integrating Uncertainties and Local Maps Federations
,
2000,
Int. J. Robotics Res..