Identification of Black Spots Based on Reliability Approach

  • Ahmadreza Ghaffari
  • Ali Tavakoli Kashani
  • Sayedbahman Moghimidarzi
Keywords: Black-spots identification, Reliability analysis, Empirical Bayesian method


Identifying crash “black-spots”, “hot-spots” or “high-risk” locations is one of the most important and prevalent concerns in traffic safety and various methods have been devised and presented for solving this issue until now. In this paper, a new method based on the reliability analysis is presented to identify black-spots. Reliability analysis has an ordered framework to consider the probabilistic nature of engineering problems, so crashes with their probabilistic na -ture can be applied. In this study, the application of this new method was compared with the commonly implemented Frequency and Empirical Bayesian methods using simulated data. The results indicated that the traditional methods can lead to an inconsistent prediction due to their inconsider -ation of the variance of the number of crashes in each site and their dependence on the mean of the data.


[1] Cheng, W., Washington, S.: Experimental Evaluation of Hotspot Identification Methods, Accident Analysis and Prevention, Vol. 37, pp. 870–881, 2005

[2] Hauer, E. , Persaud, B.N. : Problem of Identifying Hazardous Locations using Accident Data, Transportation Research Record, Vol. 975, pp. 36–43, 1984

[3] Elvik, R.: The Predictive Validity of Empirical Bayes Estimates of Road Safety , Accident Analysis and Prevention, Vol. 40, pp. 1964–1969, 2008

[4] Tarko, A.P. , Kanodia, M.: Effective and Fair Identification of Hazardous Locations, 83th Annual Meeting of
the Transportation Research Board, 2004

[5] Geurts, K., Wets, G., Brijs, T., Vanhoof, K. : Identification and Ranking of Black Spots: Sensitivity Analysis,
Transportation Research Record, Vol. 1897, pp. 34–42, 2004

[6] Miranda-Moreno, LF.: Statistical Models and Methods for the Identification of Hazardous Locations for Safety
Improvements, Ph.D. Thesis, Department of Civil Engineering, University of Waterloo, 2006

[7] Milton, J.C., Shankar, V.N. , Mannering, F.L.: Highway Accident Severities and the Mixed Logit Model: An Exploratory Empirical Analysis , Accident Analysis and Prevention, Vol. 40, pp. 260–266, 2008

[8] Snabjoornsson, J.T., Bakerb, C.J., Sigbjoornsson, R.:Probabilistic Assessment of Road Vehicle Safety in Windy Environments, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 95, pp. 1445–1462, 2008

[9] Snabjornsson, J.T. , Sigbjoornsson, R.: Probabilistic Assessment of Wind Related Accidents of Road Vehicles:
A reliability Approach , Journal of Wind Engineering and Industrial Aerodynamics, Vol. 74-76, pp. 1079-1090, 1998

[10] Zio, E. , Sansavini, G. : An Analytical Approach to the Safety of Road Network, International Journal of Reliability, Quality and Safety Engineering, Vol. 15, No. 1, pp. 67–76, 2007

[11] Sayeed, T., Navin, T., Abdelwahab, W. : A Countermeas-ure-Based Approach for Identifying and Treating Accident Prone Locations . Can. J. Civ. Eng. Vol. 24, 1997

[12] Brijs, T., Karlis, D. , Bossche, F. , Wets, G.: A Model for Identifying and Ranking Dangerous Accident Locations: A Case-Study in Flanders , Journal of Statistica-Neerlandica, Vol. 60, pp. 457-476, 2003

[13] Zheng, X. , Liu, M. : An Overview of Accident Forecasting Methodologies, Journal of Loss Prevention in the Process Industries, Vol. 22, pp. 505–512, 2009

[14] Halder, A., Mahadevan, S.: Probability, Reliability and Statistical Method in Engineering Design , John Wily and Sons, New York, 2000

[15] Hasofer, A.M. , Lind, N.C.: Exact and Invariant Second Moment Code Format, Journal of the Engineering Mechanics Division, ASCE, Vol. 100, No. EM1, pp. 111-121, 1974

[16] Rackwitz, R.: Practical Probabilistic Approach to De-sign , Bulletin No. 112, Comite European du Beton, Paris, France, 1976.

[17] Rackwitz, R., Fiessler, B. : Note on Discrete Safety checking When using non-normal Stochastic Models for basic Variables , Lord Project working Session, MIT, Cambridge, MA, June, 1976

[18] Chen, X. , Lind, N.C.: Fast probability Integration by Three-Parameter Normal Tail Approximation , Structur -al Safety, Vol. 1, pp. 269-276, 1983

[19] Fiessler, B. , Neumann, H.j. Rackwitz, R.: Quadratic Limit State in Structural Reliability , Journal of the Engineering Mechanics, ASCE, Vol. 1095, No. 4, pp. 661-676, 1979

[20] Ayyub, B.M. , Halder, A.: Practical Structural Reliability Technique, Journal of Structural Engineering, ASCE, Vol. 110, No. 8, pp. 1707-1724, 1984

[21] Rumar, K. Elsenaar, P. Marie, B. : Road Safety Manual recommendations from the World Road Association ,
PARC Technical committee on road safety, World Road Association, 2003
How to Cite
Ghaffari A, Kashani AT, Moghimidarzi S. Identification of Black Spots Based on Reliability Approach. Promet - Traffic & Transportation [Internet]. 1 [cited 23Sep.2018];25(6):525-32. Available from: