The Research of Car Rear-End Warning Model Based on MAS and Behavior

The distance between vehicles measurement is the only factor in traditional car rear-end alarm system. An alarming model based on MAS(Multi-Agent Systems) and driver´s behavior is proposed to address the above problem. It is composed of four different types of agent, interface-agent, features-extraction-agent, recognition- agent and alarm-agent, which can either work alone or collaboration through a communication protocol based on the extended KQML. The rear-end alarming algorithm utilize Bayes decision theory to calculate the probability of collision and prevent its occurrence real-time. So autonomy and reliability was enhanced in the proposed system. The effectiveness and robustness of the model have been confirmed by the simulated experiments.