An ITS for traffic accident processing based on CBR and BR

In this paper, an intelligent transportation system for traffic accident processing is introduced. In the system, the artificial nervous networks are trained and build to retrieve the similar case from the typical case base. Bayesian networks are set up to analyze the key influence factors. In the analysis of cause of the accident, the system combines the conclusion based on CBR with the conclusion based on Bayesian network Reasoning (BR), and provides to the decision-maker. Then, the decision-maker makes a conclusion of the analysis of the cause of the accident. At last, by rule reasoning, the system makes the report of responsibility cognizance and punishments. In addition, Intelligent Searching System base on the Semantic network can find the road traffic laws and regulations, the generalized model intelligent operator can calculate accurately, and the multi-base cooperation machine can coordinate database, model-base, knowledge-base and so on.