An optimal algorithm which can help traffic managers to make more accurate decisions from previous road accident case knowledge has been proposed. The algorithm based on k-nearest neighbor determines weight value of each accident case feature based on information entropy index, establishes a road accident case retrieval base using two-step cluster algorithm, and proposes a global similarity model of road accident cases. Then, a new comprehensive evaluation index called matching degree is presented. And then, a prototype system is developed to conduct case retrieval experiments to verify the performance of the proposed algorithm for road accident case retrieval. The result of the experiments clearly demonstrates the effectiveness of this case retrieval algorithm for road accident management in real time.

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