Detection, Prediction, and Avoidance of Dynamic Obstacles in Urban Environments

David Ferguson , Michael Darms, Christopher Urmson, and Sascha Kolski
Proceedings of the 2008 IEEE Intelligent Vehicles Symposium, July, 2008, pp. 1149-1154.


Download
  • Adobe portable document format (pdf) (1MB)
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.

Abstract
We present an approach for robust detection, prediction, and avoidance of dynamic obstacles in urban environments. After detecting a dynamic obstacle, our approach exploits structure in the environment where possible to generate a set of likely hypotheses for the future behavior of the obstacle and efficiently incorporates these hypotheses into the planning process to produce safe actions. The techniques presented are very general and can be used with a wide range of sensors and planning algorithms. We present results from an implementation on an autonomous passenger vehicle that has traveled thousands of miles in populated urban environments and won first place in the DARPA Urban Challenge.

Notes
Associated Center(s) / Consortia: Field Robotics Center
Associated Project(s): Urban Challenge and Tartan Racing
Number of pages: 6

Text Reference
David Ferguson , Michael Darms, Christopher Urmson, and Sascha Kolski, "Detection, Prediction, and Avoidance of Dynamic Obstacles in Urban Environments," Proceedings of the 2008 IEEE Intelligent Vehicles Symposium, July, 2008, pp. 1149-1154.

BibTeX Reference
@inproceedings{Ferguson__2008_6188,
   author = "David {Ferguson } and Michael Darms and Christopher Urmson and Sascha Kolski",
   title = "Detection, Prediction, and Avoidance of Dynamic Obstacles in Urban Environments",
   booktitle = "Proceedings of the 2008 IEEE Intelligent Vehicles Symposium",
   pages = "1149-1154",
   publisher = "IEEE",
   address = "Eindhofen",
   month = "July",
   year = "2008",
}