| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 723285 | IFAC Proceedings Volumes | 2007 | 6 Pages |
Abstract
The development of ADAS (Advance Driver Assistance Systems) increasing security of the driver implies the use of a rigorous method for their design and evaluation. Driving simulators allow rapid prototyping of ADAS systems and ease their evaluation. However, the conducted experimental tests lead to huge amount of heterogeneous data and thus require a complex data analysis process.In this paper, we propose the use of a statistical exploratory data analysis method to explore large experimental data bases in order to put forward the most significant information they include. This method is illustrated on an application to the evaluation of a collision avoidance system in car driving.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
