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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
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