Research On The Comparison And Improvement Of Road Traffic Black-Spots Identification Methods

It's believed that road traffic accident is one of public hazard incidents in the world. About two thousand people died or injured everyday just in China. However, it's very dangerous to people's lives and works, it's an urgent and important research work for studying accident characteristics and methods in order to reduce the quantity and grade of accidents, decrease economic losses and improve traffic conditions.Traffic accident black-spots are the hazard locations where there are much more accidents happened. The proportion of road in black-spots is lower, but the quantity of accident is much higher. Studying black-spots characteristics is beneficial for finding out the reasons and characteristics, and then achieving the rules of accidents. Identifying black-spots locations and adopting pertinence measures accurately are able to decrease accident quantity or grade with lesser investment, achieving a multiplier effect, so it's becoming the focus of the road traffic safety field.In this dissertation, the present typical methods of identification were classified by different indexes in domestic and abroad, and then comparing with the technique indexes, applying conditions, advantages and disadvantages. Based on the analysis of the grade of traffic accident, using equivalent accident quantity instead of accident quantity, and then analyzing its statistic distribution characteristic, the quality-control method was modified. In sight of forecasting traffic accident, we modified the fuzzy evaluation method in order to evaluate road safety level. In this method, the key questions were determining the membership functions and weights of different indexes, so the fuzzy statistical method and Delphi method were used respectively. We put forward the fuzzy cluster method to identify traffic accidents basing on the data mining theory. Finally, we gave the examples of the modified quality-control method, fuzzy evaluation method and fuzzy cluster method.From the above study, some achievements were got. Traffic accident black-spots identification methods were ranked three categories, accident quantity method, accident rate method, and synthesized method with different indexes. With strong function of Weibull distribution function, Weibull model was used to fit the equivalent accident quantity, and then the corrected accident rate curve was built up and equivalent accident rate was computed, so the quality-control method was modified. In order to predict the potential traffic accident black-spots, we modified the fuzzy evaluation identification method. We built up the fuzzy cluster identification method. Lastly, we developed the programs system of the typical traffic accident black-spots identification methods.