The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

In order to be deployed in real-world driving environments, autonomous vehicles must be able to recognize and respond to exceptional road conditions, such as highway workzones, because such unusual events can alter previously known traffic rules and road geometry. In this paper, we present a set of computer vision methods which recognize the bounds of a highway workzone and temporary changes in highway driving environments through recognition of workzone signs. Our approach filters out irrelevant image regions, localizes potential sign image regions using a learned color model, and recognizes signs through classification. Performance of individual unit tests is promising; still, it is unrealistic to expect perfect performance in sign recognition. Performance errors with individual modules in sign recognition will cause our system to misread temporary highway changes. To handle potential recognition errors, our method utilizes the temporal redundancy of sign occurrences and their corresponding classification decisions. Through testing, using video data recorded under various weather conditions, our approach was able to perfectly identify the boundaries of workzones and robustly detect a majority of driving condition changes.

Keywords

Highway workzone recognition, sign recognition, handling of potential sign recognition errors, computer vision, machine learning, self-driving car

Notes

Sponsor: the General Motors-Carnegie Mellon University Autonomous Driving Collaborative Research Laboratory (AD-CRL).

Associated Center(s) / Consortia: Field Robotics Center

Associated Project(s): Robust Detection of Highway Work Zones

Text Reference

Young-Woo Seo, David Wettergreen, and Wende Zhang , "Recognizing Temporary Changes on Highways for Reliable Autonomous Driving," Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics , October, 2012, pp. 3021-3026.

BibTeX Reference

@inproceedings{Seo_2012_7303,
   author = "Young-Woo Seo and David Wettergreen and Wende Zhang ",
   title = "Recognizing Temporary Changes on Highways for Reliable Autonomous Driving",
   booktitle = "Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics ",
   pages = "3021-3026",
   month = "October",
   year = "2012",
}

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