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Modelling on Pedestrian Accidents in Malaysia

机译：以马来西亚的行人事故为模型

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Malaysia has been experiencing rapid growth in population, economy and motorization. This increase in population and motorization has led to the increase in the number of pedestrian accidents on road networks. Recently, road safety has become a major concern for many countries including Malaysia. Many researches pertaining to the pedestrian accident data has been conducted in aiming to reduce the rate of pedestrian accidents in Malaysia. The main aim of this study is to identify which distribution is the best fitted for pedestrian accident data obtained from 30 locations in Malaysia from year 2006 to 2008. It is found that Negative Binomial distribution provides a better fit for daytime and night-time of pedestrian accident data as compared to the Poisson distribution. This study also emphasized on the identification of pedestrian accident blackspots using hierarchical Bayesian approach based on the correlation between the mean number of pedestrian accidents during night-time and daytime. This study reveals that Tapah emerged as the top ranked pedestrian accident location in this period.
机译：马来西亚一直在人口，经济和机动化方面经历快速增长。人口和机动化的增加导致道路网络上的行人事故数量增加。最近，道路安全已成为包括马来西亚在内的许多国家的主要关注。为了减少马来西亚的行人事故发生率，已经进行了许多有关行人事故数据的研究。这项研究的主要目的是确定哪种分布最适合2006年至2008年从马来西亚30个地点获得的行人交通事故数据。发现负二项式分布更适合行人的白天和晚上与Poisson分布相比的事故数据。这项研究还强调了基于层次的贝叶斯方法识别行人交通事故黑点，该方法基于夜间和白天行人事故的平均次数之间的相关性。这项研究表明，塔帕（Tapah）在此期间成为行人交通事故地点中排名最高的位置。

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