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Abstract

This paper introduces a robust prediction- and costfunction based algorithm for autonomous freeway driving. A prediction engine is built so that the autonomous vehicle is able to estimate human drivers' intentions. A cost function library is used to help behavior planners generate the best strategies. Finally, the algorithm is tested in a real-time vehicle simulation platform used by the Tartan Racing Team for the DARPA Urban Challenge 2007.

Keywords

autonomous driving, cost function, prediction

Notes

Sponsor: General Motors

Associated Project(s): Robust Autonomous Freeway Driving Behaviors

Number of pages: 6

Text Reference

Junqing Wei and John M. Dolan, "A Robust Autonomous Freeway Driving Algorithm," 2009 IEEE Intelligent Vehicles Symposium, June, 2009, pp. 1015-1020.

BibTeX Reference

@inproceedings{Dolan_2009_6740,
   author = "Junqing Wei and John M Dolan",
   title = "A Robust Autonomous Freeway Driving Algorithm",
   booktitle = "2009 IEEE Intelligent Vehicles Symposium",
   pages = "1015-1020",
   month = "June",
   year = "2009",
}

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