This article concerns road safety and driving assistance. To solve this problem, we propose a data fusion architecture based on the Dempster-Shafer theory. This multilevel approach allows the management of complementary and redundant data which come from two perception systems: an omnidirectional vision sensor and a laser telemeter. The originality of this architecture is its ability to manage and propagate uncertainties from low level data until a high level information of danger given to the driver. The first part concerns the data sensor. The second part deals with the quantification of the uncertainties of the detected vehicles, followed by a determination of situations of danger and the evaluation of their level of dangerousness with the aim of supplying the driver with an indicator of global danger around the vehicle.
['Arnaud Clerentin', 'Eric Brassart', 'Laurent Delahoche', 'B Marine', 'Sonia Izri']
A Data Fusion Architecture for the Dynamic Follow-up of Vehicles