Bayesian latent class safety performance function for identifying motor vehicle crash black spots

Transportation Research Record

Volumn 2601, Issue , 2016, Pages 90-98

  Afghari, Amir Pooyan ^a   Haque, M Mazharul ^a,b   Washington, Simon ^a,b   Smyth, Tanya ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b School of Civil and Environmental Engineering   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BARIUM COMPOUNDS; BEHAVIORAL RESEARCH;

BAYESIAN; BAYESIAN NEGATIVE BINOMIAL; BLACK SPOT; EMPIRICAL BAYESIAN; LATENT CLASS; LATENT CLASS MODEL; MOTOR VEHICLE CRASHES; NEGATIVE BINOMIAL MODELS; SAFETY PERFORMANCE FUNCTION; TOTAL CRASHES;

ACCIDENTS;

EID: 85010842247     PISSN: 03611981     EISSN: 21694052     Source Type: Journal    
DOI: 10.3141/2601-11     Document Type: Article

References (26)

1. Washington, S., and M. M. Haque. On the Commonly Accepted Assumptions Regarding Observed Motor Vehicle Crash Counts at Transport System Locations. Presented at 92nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2013.
2. Rumar, K. The Role of Perceptual and Cognitive Filters in Observed Behavior. Human Behavior and Traffic Safety, Springer, New York, 1985, pp. 151-170.
3. Aguero-Valverde, J., and P. P. Jovanis. Spatial Analysis of Fatal and Injury Crashes in Pennsylvania. Accident Analysis and Prevention, Vol. 38, No. 3, 2006, pp. 618-625.
4. Mitra, S., and S. Washington. On the Significance of Omitted Variables in Intersection Crash Modeling. Accident Analysis and Prevention, Vol. 49, 2012, pp. 439-448.
5. Mitra, S., S. P. Washington, and I. van Schalkwyk. Important Omitted Spatial Variables in Safety Models: Understanding Contributing Crash Causes at Intersections. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.
6. Deacon, J. A., C. V. Zegeer, and R. C. Deen. Identification of Hazardous Rural Highway Locations. In Transportation Research Record 543, TRB, National Research Council, Washington, D.C., 1975, pp. 16-33.
7. Morin, D. A. Application of Statistical Concepts to Accident Data. In Highway Research Record 188, HRB, National Research Council, Washington, D.C., 1967, pp. 72-79.
8. Norden, M., J. Orlansky, and H. Jacobs. Application of Statistical Quality- Control Techniques to Analysis of Highway-Accident Data. In Highway Research Record 117, HRB, National Research Council, Washington, D.C., 1956, pp. 17-31.
9. Hakkert, A. S., and D. Mahalel. Estimating the Number of Accidents at Intersections from a Knowledge of the Traffic Flows on the Approaches. Accident Analysis and Prevention, Vol. 10, No. 1, 1978, pp. 69-79.
10. Hauer, E. Empirical Bayes Approach to the Estimation of "Unsafety": The Multivariate Regression Method. Accident Analysis and Prevention, Vol. 24, No. 5, 1992, pp. 457-477.
11. Miaou, S.-P., and H. Lum. Modeling Vehicle Accidents and Highway Geometric Design Relationships. Accident Analysis and Prevention, Vol. 25, No. 6, 1993, pp. 689-709.
12. Miaou, S.-P., and H. Lum. A Statistical Evaluation of the Effects of Highway Geometric Design on Truck Accident Involvements. CONF-930120-2. Oak Ridge National Laboratory, Oak Ridge, Tenn., 1993.
13. Hauer, E. On the Estimation of the Expected Number of Accidents. Accident Analysis and Prevention, Vol.18, No. 1, 1986, pp. 1-12.
14. Hauer, E. Observational Before/After Studies in Road Safety: Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety. Emerald Group Publishing, 1997.
15. Hauer, E. Identification of Sites with Promise. In Transportation Research Record 1542, TRB, National Research Council, Washington, D.C., 1996, pp. 54-60.
16. McGuigan, D. R. D. The Use of Relationships Between Road Accidents and Traffic Flow in "Black-Spot" Identification. Traffic Engineering and Control, Vol. 22, 1981.
17. McGuigan, D. R. D. Non-Junction Accident Rates and Their Use in Black-Spot Identification. Traffic Engineering and Control, Vol. 23, No. 2, 1982, pp. 60-65.
18. Cheng, W., and S. P. Washington. Experimental Evaluation of Hotspot Identification Methods. Accident Analysis and Prevention, Vol. 37, No. 5, 2005, pp. 870-881.
19. Elvik, R. State-of-the-Art Approaches to Road Accident Black Spot Management and Safety Analysis of Road Networks. Transportøkonomisk Institutt, 2007.
20. Hauer, E., J. Kononov, B. Allery, and M. Griffith. Screening the Road Network for Sites with Promise. In Transportation Research Record: Journal of the Transportation Research Board, No. 1784, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 27-32.
21. Persaud, B., C. Lyon, and T. Nguyen. Empirical Bayes Procedure for Ranking Sites for Safety Investigation by Potential for Safety Improvement. In Transportation Research Record: Journal of the Transportation Research Board, No. 1665, TRB, National Research Council, Washington, D.C., 1999, pp. 7-12.
22. Miranda-Moreno, L., L. Fu, F. Saccomanno, and A. Labbe. Alternative Risk Models for Ranking Locations for Safety Improvement. In Transportation Research Record: Journal of the Transportation Research Board, No. 1908, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 1-8.
23. Peng, Y., D. Lord, and Y. Zou. Applying the Generalized Waring Model for Investigating Sources of Variance in Motor Vehicle Crash Analysis. Accident Analysis and Prevention, Vol. 73, 2014, pp. 20-26.
24. Washington, S., M. Karlaftis, and F. Mannering. Statistical and Eco nometric Techniques for Transportation Data Analysis. CRC Press, New York, 2003.
25. Huang, H., H. C. Chin, and M. M. Haque. Empirical Evaluation of Alternative Approaches in Identifying Crash Hot Spots: Naive Ranking, Empirical Bayes, and Full Bayes Methods. In Transportation Research Record: Journal of the Transportation Research Board, No. 2103, Transportation Research Board of the National Academies, Washington, D.C., pp. 32-41.
26. Cheng, W., and S. Washington. New Criteria for Evaluating Methods of Identifying Hot Spots. In Transportation Research Record: Journal of the Transportation Research Board, No. 2083, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 76-85.