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Lin, Q. (author), Verwer, S.E. (author), Kooij, Robert (author), Mathur, Aditya (author)The availability of high-quality benchmark datasets is an important prerequisite for research and education in the cyber security domain. Datasets from realistic systems offer a platform for researchers to develop and test novel models and algorithms. Such datasets also offer students opportunities for active and project-centric learning. In...conference paper 2020
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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
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Zhang, Yihuan (author), Lin, Q. (author), Wang, Jun (author), Verwer, S.E. (author), Dolan, John M. (author)Car-following is the most general behavior in highway driving. It is crucial to recognize the cut-in intention of vehicles from an adjacent lane for safe and cooperative driving. In this paper, a method of behavior estimation is proposed to recognize and predict the lane change intentions based on the contextual traffic information. A model...journal article 2018
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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