考虑信息熵模型的道路交通安全态势模型

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分析道路交通事故统计中的交通事故数、死亡人数和受伤人数,并且将这三种统计数据和某地区的机动车辆数和机动车驾驶人数相结合,分别得到万车交通事故数和万人死亡人数和万人受伤人数,建立信息熵模型(information entropy model)对以上数据进行分析研究,从而得出评价交通安全程度的指标.这种方法突破了以往仅停留在万车死亡人数的指标上,且以往的研究方法还需采用专家评价法或德尔菲等定性评价方法,此评价方法对道路交通安全的分析更客观.最后以北京和天津近三年的交通事故统计数据为案例进行分析,研究结果表明:2012年至2014年间北京道路交通安全评价指标主要以交通事故起数认定所在年的道路交通安全状况,天津道路交通安全评价指标主以交通事故造成的受伤人数认定所在年的道路交通安全状况,且北京三个指标的G_i均高于天津,因此北京交通安全水平要低于天津. The number of traffic accidents, the number of deaths and the number of casualties in road traffic accidents statistics were analyzed. Combining these three kinds of statistics with the number of motor vehicles and the number of motor vehicles in a certain area, the number of traffic accidents per million and deaths of 10,000 The number of people and the number of wounded people, establish an information entropy model to analyze and study the above data, and get the index to evaluate the degree of traffic safety.This method breaks through the previous indicators that only stay in the number of deaths per million vehicles, In the past, the methods of expert evaluation and Delphi were also used to evaluate the road traffic safety.At last, the traffic accidents statistics in Beijing and Tianjin for the past three years were taken as examples to analyze the problem. The results show that the traffic safety assessment indicators of Beijing road traffic between 2012 and 2014 are based on the road traffic safety situation of the year when traffic accidents are identified. Traffic safety evaluation indicators of Tianjin road traffic safety mainly focus on the number of injuries caused by traffic accidents in the year of road traffic safety Status, and Beijing G_i three indicators are higher than Tianjin, Beijing traffic safety Level is lower than Tianjin.
其他文献
一、年会概况2004年8月,笔者参加了国际航空安全调查员协会成立40周年年会。本届年会在澳大利亚举办,共有334名事故调查员分别来自世界32个国家和地区,与会的40位来自世界各