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Lin, Q. (author), Zhang, Yihuan (author), Verwer, S.E. (author), Wang, Jun (author)
This paper proposes a novel hybrid model for learning discrete and continuous dynamics of car-following behaviors. Multiple modes representing driving patterns are identified by partitioning the model into groups of states. The model is visualizable and interpretable for car-following behavior recognition, traffic simulation, and human-like...
journal article 2019
document
Zhang, Yihuan (author), Lin, Q. (author), Wang, Jun (author), Verwer, S.E. (author)
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...
conference paper 2017