(Created page with " == Abstract == International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on...") |
m (Scipediacontent moved page Draft Content 438764141 to Lefevre et al 2013a) |
(No difference)
| |
Latest revision as of 20:43, 3 February 2021
Abstract
International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on Support Vector Machine and Bayesian filtering is proposed for online lane change intention prediction. The approach uses the multiclass probabilistic outputs of the Support Vector Machine as an input to the Bayesian filter, and the output of the Bayesian filter is used for the final prediction of lane changes. A lane tracker integrated in a passenger vehicle is used for real-world data collection for the purpose of training and testing. Data from different drivers on different highways were used to evaluate the robustness of the approach. The results demonstrate that the proposed approach is able to predict driver intention to change lanes on average 1.3 seconds in advance, with a maximum prediction horizon of 3.29 seconds.
Original document
The different versions of the original document can be found in:
Document information
Published on 01/01/2013
Volume 2013, 2013
DOI: 10.1109/ivs.2013.6629564
Licence: CC BY-NC-SA license
Share this document
Keywords
claim authorship
Are you one of the authors of this document?