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Car-following Behavior Model Learning Using Timed Automata

Conference Paper (2017)
Author(s)

Yihuan Zhang (Tongji University)

Qin Lin (TU Delft - Cyber Security)

Jun Wang (Tongji University)

Sicco Verwer (TU Delft - Cyber Security)

Research Group
Cyber Security
Copyright
© 2017 Yihuan Zhang, Q. Lin, Jun Wang, S.E. Verwer
DOI related publication
https://doi.org/10.1016/j.ifacol.2017.08.423
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 Yihuan Zhang, Q. Lin, Jun Wang, S.E. Verwer
Research Group
Cyber Security
Pages (from-to)
2353-2358
Reuse Rights

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Abstract

Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common state sequences are extracted from the model and clustered as driving patterns. The Next Generation SIMulation dataset on the I-80 highway is used for learning and evaluating. The experimental results demonstrate high accuracy of car-following model fitting.