AN APPROACH-BASED CRASH ANALYSIS AND APPRAISAL MODEL FOR SAFETY DESIGN AND MANAGEMENT

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概要

• 論文の詳細を見る

• This research focuses on examining the interacting relationship between vehicle crashes and road engineering factors. The back-propagation artificial neural network (BPN) method with feed-forward structure is used to develop the model. Each intersection is decomposed into several approach sets to establish the proposed microscopic relationship with vehicle crashes. A total of 1,225 records at 69 primary/secondary intersections in Tainan, Taiwan, were used to calibrate the bi-level models of 11 crash types. First is a distinguish model to tell if an approach set will have crash; the second is a prediction model to forecast crash numbers by type for each approach set. Error rates for all distinguish models are under 15% with an average of 6.1%. Error rates for all prediction models are under 25% with an average of 6.7%. An overall RMS is 0.1617. Practical field test also proves model's validity.

• Eastern Asia Society for Transportation Studiesの論文

著者

• HWANG Kevin

  Department of Transportation, Communication and Management Science National Cheng-Kung University

• HWANG Kevin

  Department of Transportation and Communication Management Science National Cheng-Kung University

• WEI Kai-Yuan

  Operations Strategy Dept., Operations & Maintenance Division Taiwan High Speed Rail Corporation

関連論文

• AN APPROACH-BASED CRASH ANALYSIS AND APPRAISAL MODEL FOR SAFETY DESIGN AND MANAGEMENT

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