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A Partial Proportional Odds Model for Pedestrian Crashes at Mid-Blocks in Melbourne Metropolitan Area

机译:墨尔本都会区中区行人交通事故的部分比例赔率模型

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Pedestrian crashes account for 11% of all reported traffic crashes in Melbourne metropolitan area between 2004 and 2013. There are very limited studies on pedestrian accidents at mid-blocks. Mid-block crashes account for about 46% of the total pedestrian crashes in Melbourne metropolitan area. Meanwhile, about 50% of all pedestrian fatalities occur at mid-blocks. In this research, Partial Proportional Odds (PPO) model is applied to examine vehicle-pedestrian crash severity at mid-blocks in Melbourne metropolitan area. The PPO model is a logistic regression model that allows the covariates that meet the proportional odds assumption to affect different crash severity levels with the same magnitude; whereas the covariates that do not meet the proportional odds assumption can have different effects on different severity levels. In this research vehicle-pedestrian crashes at mid-blocks are analysed for first time. In addition, some factors such as distance of crashes to public transport stops, average road slope and some social characteristics are considered to develop the model in this research for first time. Results of PPO model show that speed limit, light condition, pedestrian age and gender, and vehicle type are the most significant factors that influence vehicle-pedestrian crash severity at mid-blocks.
机译:在2004年至2013年之间,行人交通事故占墨尔本市区报告的所有交通事故的11%。关于街区中段行人交通事故的研究非常有限。街区中段的撞车事故约占墨尔本市区行人交通事故的46%。同时,所有行人死亡中约有50%发生在街区中间。在这项研究中,部分比例赔率(PPO)模型用于检验墨尔本市区中街区的行人交通事故严重程度。 PPO模型是一个逻辑回归模型,它允许满足比例赔率假设的协变量以相同的幅度影响不同的碰撞严重性级别;而不符合比例赔率假设的协变量可能会对不同的严重程度产生不同的影响。在本研究中,首次对中段车辆行人碰撞进行了分析。此外,本研究首次考虑了诸如到公共交通站点的碰撞距离,平均道路坡度和一些社会特征等因素来开发该模型。 PPO模型的结果表明,速度限制,光线条件,行人年龄和性别以及车辆类型是影响中段车辆行人碰撞严重程度的最重要因素。

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