MATEC Web Conf.
Volume 103, 2017International Symposium on Civil and Environmental Engineering 2016 (ISCEE 2016)
|Number of page(s)||8|
|Section||Traffic Behaviour and Road Safety Engineering|
|Published online||05 April 2017|
Road Fatality Model Based on Over-Dispersion Data Along Federal Route F0050
Smart Driving Research Center (SDRC), Faculty of Civil and Environmental Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
* Corresponding author: firstname.lastname@example.org
According to The World Health Ranking 2011 has ranked Malaysia as 20th in its list of countries with the most deaths caused by road accidents. Road accidents also have been identified as the prime cause of death in Malaysia after the heart disease, stroke, influenza and pneumonia. To date, previous researches from Malaysian Institute of Road Safety (MIROS) have reported that averages of 18 people were killed on Malaysian road daily. There are many kinds of models that have been developed in modelling the circumstance of accidents. The most widely applied was Poisson and Negative Binomial regression models while Zeroinflated Poisson and Zero-inflated Negative Binomial are the modification of Poisson and Negative Binomials regression models. This study interested to focus on road F0050 as statistic data from Royal Malaysian Police 2014 list F0050 as one of the high accident road in Malaysia from kilometre 0 until kilometre 58. R programming was chose to analyse the relationship between road fatality and its factor (annual average daily traffic (AADT), speed, shoulder width, lane width). Negative binomial and Zero-inflated negative binomial (ZINB) were shown to be preferred modelling methods for this study. Significant positive relationships were also identified between road fatality and annual average daily traffic (AADT) and lane width. This relationship can be a helpful support to the decision making of accident management for road F0050.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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