Application of Poisson random effect models for highway network screening

Accident Analysis and Prevention

Volumn 63, Issue , 2014, Pages 74-82

  Jiang, Ximiao ^a   Abdel Aty, Mohamed ^a   Alamili, Samer ^a  

^a University of Central Florida   (United States)

Author keywords

Empirical Bayesian; Full Bayesian; Hotspot identification; Network screening; Poisson Log Normal; Random effect

Indexed keywords

BAYESIAN; EMPIRICAL BAYESIAN; HOT SPOT; LOG-NORMAL; RANDOM EFFECTS;

RISK ASSESSMENT;

RANDOM PROCESSES;

ARTICLE; BAYES THEOREM; EMPIRICAL BAYESIAN; ENVIRONMENTAL PLANNING; FULL BAYESIAN; HOTSPOT IDENTIFICATION; HUMAN; NETWORK SCREENING; POISSON DISTRIBUTION; POISSON LOG-NORMAL; RANDOM EFFECT; RISK ASSESSMENT; SAFETY; SPATIOTEMPORAL ANALYSIS; STATISTICAL MODEL; STATISTICS; TIME; TRAFFIC ACCIDENT;

EMPIRICAL BAYESIAN; FULL BAYESIAN; HOTSPOT IDENTIFICATION; NETWORK SCREENING; POISSON LOG-NORMAL; RANDOM EFFECT;

ACCIDENTS, TRAFFIC; BAYES THEOREM; ENVIRONMENT DESIGN; HUMANS; MODELS, STATISTICAL; POISSON DISTRIBUTION; RISK ASSESSMENT; SAFETY; SPATIO-TEMPORAL ANALYSIS; TIME FACTORS;

EID: 84888313409     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2013.10.029     Document Type: Article

References (29)

1. J. Aguero-Valverde, and P.P. Jovanis Bayesian multivariate Poisson log-normal models for crash severity modeling and site ranking Presented at the 88th Annual Meeting of the Transportation Research Board 2009
2. P. Alluri Assessment of potential site selection methods for use in prioritizing safety improvements on Georgia roadways. M. Sc. Thesis 2008 Clemson University
3. C. Caliendo, M. Guida, and A. Parisi A crash-prediction model for multilane roads Accident Analysis and Prevention 39 2007 657 670 (Pubitemid 46661833)
4. B.P. Carlin, and T.A. Louis Bayes and Empirical Bayes Methods for Data Analysis, Monographs on Statistics and Applied Probability 69 2000 Chapman & Hall London
5. W. Cheng, and S. Washington New criteria for evaluating methods of identifying hot spots Transportation Research Record 2083 2008 76 85
6. H.C. Chin, and M.A. Quddus Applying the random effect negative binomial model to examine traffic accident occurrence at signalized intersections Accident Analysis and Prevention 35 2003 253 259
7. W. Greene Econometric Analysis 4th ed. 2000 Prentice Hall New Jersey
8. E. Hauer Observational Before-After Studies in Road Safety 1997 Pergamon Press Tarrytown, N.Y.
9. J.L. Higle, and M.B. Hecht A Comparison of Techniques for the Identification of Hazardous Locations. In Transportation Research Record 1238, TRB 1989 National Research Council Washington, D.C. 10 19
10. P.D. Hoff A First Course in Bayesian Statistical Methods 2009 Springe Dordrecht Heidelberg London, New York 45 48
11. H.L. Huang, H.C. Chin, and M.M. Haque Hotspot identification: a full Bayesian hierarchical modeling approach Transportation and Traffic Theory 2009 441 462 http://link.springer.com/chapter/10.1007/978-1-4419-0820-9-22
12. X.M. Jiang, B.S. Huang, R. Zaretzki, S. Richards, and X.D. Yan Estimating safety effects of pavement management factors utilizing Bayesian random effect models Traffic Injury Prevention 2013 10.1080/15389588.2012.756582
13. S.C. Joshua, and N.J. Garber Estimating truck accident rate and involvements using linear and Poisson regression models Transportation Planning and Technology 15 1990 41 58
14. P.P. Jovanis, and H.L. Chang Modeling the relationship of accidents to miles traveled Transportation Research Record 1068 1986 42 51
15. D. Lord, and F.L. Mannering The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives Transportation Research Part A 44 5 2010 291 305
16. J.M. Ma, K.M. Kockelman, and P. Damien A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods Accident Analysis and Prevention 40 2008 964 975
17. M.J. Maher, and L.J. Mountain The identification of accident blackspots: a comparison of current methods Accident Analysis and Prevention 20 2 1988 143 151 (Pubitemid 18591785)
18. D.R.D. McGuigan The use of relationships between road accidents and traffic flow in "blackspot" identification Traffic Engineering and Control 22 8/9 1981 448 451 453
19. D.R.D. McGuigan Non-junction accident rates and their use in "black-spot" identification Traffic Engineering and Control 23 2 1982 60 65
20. S.P. Miaou, and H. Lum Modeling vehicle accidents and highway geometric design relationships Accident Analysis and Prevention 25 1993 689 709
21. A. Montella A comparative analysis of hotspot identification methods Accident Analysis and Prevention 42 2010 571 581
22. E.-S. Park, and D. Lord Multivariate Poisson-lognormal models for jointly modeling crash frequency by severity Transportation Research Record 2019 2007 1 6 (Pubitemid 351472915)
23. B.N. Persaud Empirical Bayes procedure for ranking sites for safety investigation by potential for safety improvement Transportation Research Record 1665 1999 7 12
24. V.N. Shankar, R.B. Albin, J.C. Milton, and F.L. Mannering Evaluating median crossover likelihoods with clustered accident counts: an empirical inquiry using the random effects negative binomial model Transportation Research Record 1635 1998 44 48 (Pubitemid 128553734)
25. D.J. Spiegelhalter, N.G. Best, B.P. Carlin, and V.D. Linde Bayesian measures of model complexity and fit (with discussion) Journal of the Royal Statistical Society B64 4 2003 583 616
26. U.S. Department of Transportation Transportation equity act for the 21st century (TEA-21). Washington, D.C. 1998
27. U.S. Department of Transportation Safe, Accountable, Flexible, Efficient, Transportation Equity Act: A Legacy for Users (SAFETEA-LU). Washington, D.C. 2009
28. G.F. Ulfarsson, and V.N. Shankar Accident count model based on multiyear cross-sectional roadway data with serial correlation Transportation Research Record 1840 2003 193 197
29. S. Washington, and W. Cheng High Risk Crash Analysis. FHWA-AZ-05-558 December 2005 Arizona Department of Transportation Phoenix