MOHA
A Multi-Mode Hybrid Automaton Model for Learning Car-Following Behaviors
Qin Lin (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Yihuan Zhang (Tongji University)
Sicco Verwer (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Jun Wang (Tongji University)
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Abstract
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 cruise control. The experimental results using the next generation simulation datasets demonstrate its superior fitting accuracy over conventional models.