Research on commuter's travel behavior faced to multi-agent under pre-trip information

Authors studied the commuter's travel behavior under advanced traffic information system (ATIS) pre-trip information based on the combination of multi-agent and micro-simulation methods. Firstly, a perception dynamic updating model which commuters update their travel time perceptions by Bayesian theory in light of pre-trip information and their previous experiences. Then, based on the belief-desire-intention (BDI) model, every commuter-vehicle unit was described as an agent which possesses a two-layer architecture and decision-making mechanism of agent travel behavior was specified by extended AgentSpeak(L) language. Finally, a simple simulation test was carried out by combination of Jason and Paramics. The simulation results show that the Bayesian theory can effectively explain the commuter's travel dynamics behavior and the combination of multi-agent technology and micro-simulation is a new way of studying driver's behavior.