عنوان مقاله [English]
Identiﬁcation of hot spots is an important activity for improving the overall safety of roadway networks. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. In this research, The seven commonly applied HSID methods (accident frequency (AF), equivalent property damage only (EPDO) based the coefficients of the PIARC, 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 (the site consistency test, the method consistency test, the total rank differences test, the 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 hotspots in subsequent time periods .To evaluate the HSID methods, three years of crash data from the Jiroft-Kerman road 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. Also the quantitative evaluation tests showed that the EB method is the most consistent method for identifying hotspots and accident frequency, accident rate and combined criteria methods after EB method cause the identification of hotspots similar, that they have similar performance and their evaluation results is the same, have the best performance. Following these methods, the P-value, equivalent property damage only based the coefficients PIARC, and societal risk-based respectively. Societal
risk-based method performed worst in all of the tests. It should be noted that advantages associated with the EB method were based on crash data from one the road Iran country and 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., Soori, H. (2006), “Epidemiology of death from injuries in the Islamic Republic of Iran”. East Mediterr Health J. May-Jul; 12(3-4),
-World Health Organization. (2009), “Global status report on road safety: time for action”. World Health Organization.
-Hatamabadi, H. R., Vafaee, R., Hadadi, M., Abdalvand, A., Esnaashari, H. R., 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.
-ROSPA (2002), The Royal Society for Prevention of Accidents. “Road safety engineering manual”. Birmingham.
-TAC (2004), Transportation Association of Canada. “The Canadian guide to In-Service road safety reviews”. Ottawa.
-Tarko, A. P., Kanodia, M (2004), Hazard Elimination Program. “Manual on improving safety of Indiana road intersections and sections”. Report FHWA/IN/JTRP2003/19, West Lafayette, Indiana.
-Lyon, C., Gotts, B., Wong, W .K. F., Persaud, B. (2007), “Comparison of alternative methods for identifying sites with high proportion of specific accident types”. Transportation Research Record, 2019. TRB, National Research Council, Washington, DC, PP. 212-218.
-Cheng, W., Washington, S. (2005), “Experimental evaluation of hotspots identification methods”. Accident Analysis and Prevention, Vol. 37, pp. 870-881.
-Cheng, W., Washington, S. (2008), “New criteria for evaluating methods of identifying Hotspots”. Transportation Research Record, 2083. TRB, National Research Council, Washington DC. PP. 76-85.
-Elvik, R. (2008), “Comparative analysis of techniques for identifying hazardous road locations”. Transportation Research Record, 2083. TRB, National Research Council, Washington DC. PP. 72-75.
-Persaud, B., Lyon, C., 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. pp. 7-12.
-Montella, A. (2010) , “A comparative analysis of Hotspots identification method”. Accident Analysis & Prevention, Vol. 42,
-Yu, H., Liu, P., Chen, J., Wang, H. (2014), “Comparative analysis of the spatial analysis methods for Hotspots identification”. Accident Analysis & Prevention.
-Qu, X., Meng, Q. (2014), “A note on hotspots identification for urban expressways”. Safety Science, Vol. 66,
-PIARC (2004), World Road Association, Technical committee on road safety C13. Road Safety Manual.
-Washington, S., Haque, M. M., Oh, J., Lee, D. (2014), “Applying quantile regression for modeling equivalent property damage only crashes to identify accident Blackspots”. Accident Analysis & Prevention, Vol. 66,
-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).