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An accident prediction model for divided highways: a case study of Trabzon coastal divided highway

机译:公路分割事故预测模型-以特拉布宗沿海公路分割为例

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Traffic accidents in Turkey have been increasing every year. Although serious property damage and fatalities have occurred in accidents, Turkey hasn't sufficiently overcome this problem. The main objective for this study is to investigate the factors which cause accidents and to create an accident prediction model which includes relationships between these factors. With this model, the expected number of accidents at divided highways can be predicted and suitable measures for providing road safety can be defined. For this study, 5 years' (2002, 2003, 2004, 2006 and 2007) accident data of 113.5 km road sections of Trabzon coastal divided highway, traffic and highway characteristics of these sections were collected, then an accident prediction model was formed. The technique of generalized linear models (GLMs) was applied to the data. Because of over dispersion of Poisson regression model, a Negative Binomial regression model was found to be the most appropriate approach for analysis of this data. This model indicates that the vehicle kilometres of travel, the number of pedestrian crossing and average posted speed are significant variables on traffic accident occurrences.
机译:土耳其的交通事故每年都在增加。尽管事故中发生了严重的财产损失和死亡事故,但土耳其仍未能充分克服这一问题。这项研究的主要目的是调查导致事故的因素,并创建一个包括这些因素之间关系的事故预测模型。使用此模型,可以预测在分开的高速公路上发生的预期事故数量,并且可以定义用于提供道路安全的适当措施。本研究收集了特拉布宗沿岸公路113.5 km的5年(2002年,2003年,2004年,2006年和2007年)事故数据,并分析了这些路段的交通和高速公路特征,然后建立了事故预测模型。广义线性模型(GLM)技术已应用于数据。由于Poisson回归模型的过度分散,负二项式回归模型被认为是分析此数据的最合适方法。该模型表明,车辆行驶的公里数,人行横道的数量和平均张贴速度是交通事故发生的重要变量。

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