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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References
Al-Masaeid HR, Al-Mashakbeh AA, Qudah AM (1999) Economic costs of traffic accidents in Jordan. Accident Analysis and Prevention 31:347–357
Baguley CJ (1995) Interim Guide on Identifying, Prioritising and Treating Hazardous Locations on Roads in Malaysia. Public Works Department, Malaysia
Downing A (1997) Accident cost in Indonesia: A review. Overseas Centre Transport Research Laboratory Crowthorne Berkshire United Kingdom, RG456AU
Elvik R (1997) Evaluations of road accident blackspot treatment: A case of the iron law of evaluation studies? Accident Analysis and Prevention 29(2):19–199
Geurts K, Wets G, Vanhoof K (2005) Ranking and selecting dangerous accident locations: Case study. Urban Transport 77:229–238
MacNab YC (2003) A Bayesian hierarchical model for accident and injury surveillance. Accident Analysis and Prevention 35:91–102
Miaou SP (1994) The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions. Accident Analysis and Prevention 26(4):471–482
Noorizam Daud, Kamarulzaman Ibrahim (2007) Taburan Nisbah Kos Kemalangan Maut dan Cedera Parah. Jurnal Teknologi Maklumat dan Sains Kuantitatif. Universiti Teknologi MARA. Jilid 6
Radin Umar (1998) Critical review of the status of road safety in Malaysia. Journal Chartered Institute of Transport, UK 7(1):20–40
Schlüter PJ, Deely JJ, Nicholson J (1997) Ranking and selecting motor vehicle accident sites by using a hierarchical Bayesian model. The Statistician 46(3):293–316
Spiegelhalter DJ, Thomas A, Best NG, Lunn D (2003) WinBUGS Version 1.4 User Manual.Cambridge: Medical Research Council & Imperial College, UK. http://www.mrc-bsu.cam.ac.uk/bugs
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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