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. Terms-Hybrid automaton, car-following behavior, simulation and control.
MOHA is a novel model for learning car-following behaviors using a hybrid automaton recently proposed in REF .
MOHA: A Multi-Mode Hybrid Automaton Model for Learning Car-Following Behaviors
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Engineering Computer Science