Evaluation and Statistical Validation of Black-Spots Identification Methods

Document Type : Research Paper


1 MSc. Grad., School of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran

2 Assistant Professor, School of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran


Despite the identification of crash hotspots as a first step of the roads safety management process, with various effective black spots identification (HSID) methods, only a few researchers have compared the performance of these methods; also it is not clear which test is the most consistent in the black-spots identification. In this research, seven commonly applied HSID methods (accident frequency (AF), PIARC coefficient based equivalent property damage only (EPDO), P-value (Islamic Republic of Iran Ministry Roads and Urban development), accident rate (AR), combined criteria, empirical Bayes (EB), societal risk-based) were compared against six robust and informative quantitative evaluation criteria (site consistency test, method consistency test, total rank differences test, total score test, sensitivity test and specificity test). These tests evaluate each method performance in a variety of areas, such as efficiency in identifying sites that show consistently poor safety performance, reliability in identifying the same black spots in subsequent time periods. To evaluate the HSID methods, three years of crash data from the Kerman state were used. Analytical Hierarchy Process (AHP) method has been used for determination the importance coefficients of evaluation tests and as a result, showed that the total rank differences test is the most appropriate test. The quantitative evaluation tests showed that the EB method performs better than the other HSID method. Test results highlight that the EB method is the most consistent and reliable method for identifying priority investigation locations. Overall, this result is consistent with the results of previous studies. The societal risk-based method performed worst in the all of the tests. It should be noted that advantages associated with the EB method were based on crash data from one of the road in Iran country, so the relative performances of HSID methods may change when using other crash data. However, the study results are consistent with earlier findings. 


- Akbari, M. E., Naghavi, M. and Soori, H. (2006) ̏ Epidemiology of death from injuries in the Islamic Republic of Iran ̋. East Mediterr Health Journal, Vol. 12, No. 3-4, pp.382-390.
- Cheng, W. qand Washington, S. (2005) ̏ Experimental evaluation of hotspots identification methods ̋. Accident Analysis and Prevention, Vol. 37, No. 5, pp. 870-881.
- Cheng, W. and Washington, S. (2008) ̏ New criteria for evaluating methods of identifying Hotspots ̋. Transportation Research Record. TRB, National Research Council, Washington, DC, No. 2083, PP. 76-85.
- Dey, P. K. and Ramcharan, E.K. (2008) ̏ Analytical Hierachy Process helps select site for limestone quarry expansion in Barbodos ̋, Journal of Environmental Management, Vol. 88, No. 4, pp. 1384-1395.
- Elvik, R. (2008) ̏ Comparative analysis of techniques for identifying hazardous road locations ̋, Transportation Research Record, TRB, National Research Council, Washington, DC, No. 2083, PP. 72-75.
- Hatamabadi, H. R., Vafaee, R., Hadadi, M., Abdalvand, A., Esnaashari, H. R. and Soori H. (2011)  ̏ Epidemiologic study of road traffic injuries by road user type charactrristics and road environment in Iran: A community based approach ̋. J Traffic Injury Prevention, Vol.13, No. 1, pp. 61-64.
- Lyon, C., Gotts, B., Wong, W .K. F. and Persaud, B. (2007) ̏ Comparison of alternative methods for identifying sites with high proportion of specific accident types ̋. Transportation Research Record, TRB, National Research Council, Washington, DC, No. 2019, pp. 212-218.
- Montella, A. (2010 ̏ (A comparative analysis of Hotspots Identification Method ̋, Accident Analysis and Prevention, Vol. 42, No 2, pp. 571-581.
- National Safety Council (2009) ̏ Estimating the costs of motor vehicle injuries ̋. http://www.nsc.org/news_resources/injury_and_death_statistics/pages/EstimatingtheCostsofUnintentionalInjuries.aspx (accessed 08.01.13).
- Ozer, I. (2007) ̏ Multi-Criteria Group Decision Marking method using AHP and Integrated Web-Based Decision support system “, MSc. Thesis, University of Ottawa, Canada.
- Persaud, B., Lyon, C. and Nguyen, T. (1999) ̏ Empirical Bayes procedure for ranking sites for safety investigation by potential for improvement ̋. Transportation Research Record, 1665. TRB, National Research Council, Washington, DC, No. 1665, pp. 7-12.
- PIARC (2004) ̏ Road Safety Manual ̋, World Road Association, Technical Committee On Road Safety C13.
- Qu, X. and Meng, Q. (2014) ̏ A note on hotspots identification for urban expressways “, Safety Science, Vol. 66, No. 2273, pp. 87-91.
- ROSPA (2002) ̏ Road safety engineering manual ̋, The Royal Society for Prevention of Accidents, Birmingham.
- Schenkerman, Stan (1994) ̏Avoiding rank-reversal in AHP decision support models ̋. European Journal of operation Research, Vol. 74, No. 3, pp. 407-419.
- Shyur, H. I. and Shih, H. S. (2006) ̏ A hybrid MCDM model for strategic Vendor selection “, Mathematical and Computer modelling. Vol. 44, No. 7-8, pp. 749-761.
- TAC (2004) ̏ The Canadian guide to In-Service road safety reviews ̋, Transportation Association of Canada, Ottawa.
- Tarko, A. P. and Kanodia, M. (2004) ̏ Hazard elimination program. manual on improving safety of Indiana road intersections and sections”,  Report FHWA/IN/JTRP2003/19, West Lafayette, Indiana.
- Vargas., Luis G. (1994) ̏ Reply to Schenkerman avoiding rank reversal in AHP decision support model ̋.  European Journal of operation Research, Vol.74, No. 3, pp. 420-425.
- World Health Organization (2009) ̏ Global status report on road safety: time for action ̋. World Health Organization. Geneva. Website: www.who.com
- Washington, S., Haque, M. M., Oh, J. and Lee, D. (2014) ̏Applying quantile regression for modeling equivalent property damage only crashes to identify accident Black-Spots ̋, Accident Analysis and Prevention, Vol. 66, No. 3, pp. 136-146.
- Yu, H., Liu, P., Chen, J. and Wang, H. (2014) ̏ Comparative analysis of the spatial analysis methods for Hotspots identification ̋,  Accident Analysis and Prevention, Vol. 66, No.3, pp.80-88.