Abstract
Road accident is an unfortunate event which is a matter of serious concern to the authority. A proactive measure taken in reducing the rate of accidents is to identify hazardous locations for treatment. In order to allocate resources wisely when treating accident locations, engineers usually rank accident locations based on the mean number of accidents observed over a period of time. Identification, ranking, and selecting hazardous accident locations from a group under consideration is a fundamental goal for traffic safety researchers. The search of a better method to carry out such tasks is the main aim of this study in order to improve road safety in the country. The number of accident varies within and between locations, hence making Bayesian hierarchical model suitable to be applied when allowing for these two stages of variation. This study will illustrate the use of posterior mean to rank accident blackspots.
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Acknowledgement
The author would like to thank the Malaysian Road Ministry of Works and the Malaysian Royal Police for providing the accident data to be used in the study. Special thanks also go to the Engineering Mathematics Research Group of UKM and UiTM.
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Daud, N., Ibrahim, K. (2009). Hierarchical Bayesian approach for ranking of accident blackspots with reference to cost of accidents. In: Mastorakis, N., Sakellaris, J. (eds) Advances in Numerical Methods. Lecture Notes in Electrical Engineering, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76483-2_15
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DOI: https://doi.org/10.1007/978-0-387-76483-2_15
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