Context-Aware Tracking of Moving Objects for Distance Keeping - Robotics Institute Carnegie Mellon University

Context-Aware Tracking of Moving Objects for Distance Keeping

Wenda Xu, Jarrod M. Snider, Junqing Wei, and John M. Dolan
Conference Paper, Proceedings of IEEE Intelligent Vehicles Symposium (IV '15), pp. 1380 - 1385, June, 2015
View Publication

Abstract

We propose a robust object tracking algorithm for distance keeping. Taking advantage of a context-based region of interest, we are able to maximize the performance of each sensor, and reduce the computation time since we only focus on the targets inside the region. Tracking targets in road coordinates enables finding the distance-keeping target on any curved road, while a commercial Adaptive Cruise Control (ACC) system works best on straight roads. We demonstrate that the overall performance of the proposed algorithm is better than that of a commercial ACC system. The distance-keeping target can either be used for lane following for a standalone ACC system or an autonomous vehicle. Our object tracking algorithm can also be extended to find the target of interest for lane changing or ramp merging for an autonomous vehicle.

BibTeX

@conference{Xu-2015-5987,
author = {Wenda Xu and Jarrod M. Snider and Junqing Wei and John M. Dolan},
title = {Context-Aware Tracking of Moving Objects for Distance Keeping},
booktitle = {Proceedings of IEEE Intelligent Vehicles Symposium (IV '15)},
year = {2015},
month = {June},
pages = {1380 - 1385},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.