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Carnegie Mellon Robotics Institute

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Abstract

In this paper, a prediction- and cost functionbased algorithm (PCB) is proposed to implement robust freeway driving in autonomous vehicles. A prediction engine is built to predict the future microscopic traffic scenarios. With the help of a human-understandable and representative cost function library, the predicted traffic scenarios are evaluated and the best control strategy is selected based on the lowest cost. The prediction- and cost function-based algorithm is verified using the simulator of the autonomous vehicle Boss from the DARPA Urban Challenge 2007. The results of both case tests and statistical tests using PCB show enhanced performance of the autonomous vehicle in performing distance keeping, lane selecting and merging on freeways.

Keywords

autonomous driving, cost function, behaviors, freeway driving

Notes

Associated Project(s): Robust Autonomous Freeway Driving Behaviors

Number of pages: 6

Text Reference

Junqing Wei, John M. Dolan, and Bakhtiar Litkouhi, "A Prediction- and Cost Function-Based Algorithm for Robust Autonomous Freeway Driving," 2010 IEEE Intelligent Vehicles Symposium, June, 2010, pp. 512-517.

BibTeX Reference

@inproceedings{Dolan_2010_6743,
   author = "Junqing Wei and John M Dolan and Bakhtiar Litkouhi",
   title = "A Prediction- and Cost Function-Based Algorithm for Robust Autonomous Freeway Driving",
   booktitle = "2010 IEEE Intelligent Vehicles Symposium",
   pages = "512-517",
   month = "June",
   year = "2010",
}

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