Table of Contents Author Guidelines Submit a Manuscript
Journal of Advanced Transportation
Volume 2017 (2017), Article ID 5391054, 8 pages
https://doi.org/10.1155/2017/5391054
Research Article

Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation

School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong 510641, China

Correspondence should be addressed to Huiying Wen; nc.ude.tucs@newyh

Received 26 June 2017; Accepted 11 September 2017; Published 24 October 2017

Academic Editor: Francesco Bella

Copyright © 2017 Qiang Zeng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Ahmed, H. Huang, M. Abdel-Aty, and B. Guevara, “Exploring a Bayesian hierarchical approach for developing safety performance functions for a mountainous freeway,” Accident Analysis & Prevention, vol. 43, no. 4, pp. 1581–1589, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. R. Yu, M. Abdel-Aty, and M. Ahmed, “Bayesian random effect models incorporating real-time weather and traffic data to investigate mountainous freeway hazardous factors,” Accident Analysis & Prevention, vol. 50, pp. 371–376, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. D. Lord and F. Mannering, “The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives,” Transportation Research Part A: Policy and Practice, vol. 44, no. 5, pp. 291–305, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. Q. Zeng, H. Huang, X. Pei, and S. C. Wong, “Modeling nonlinear relationship between crash frequency by severity and contributing factors by neural networks,” Analytic Methods in Accident Research, vol. 10, pp. 12–25, 2016. View at Publisher · View at Google Scholar · View at Scopus
  5. P. P. Jovanis and H.-L. Chang, “Modeling the relationship of accidents to miles traveled,” Transportation Research Record, pp. 42–51, 1986. View at Google Scholar · View at Scopus
  6. F. L. Mannering and C. R. Bhat, “Analytic methods in accident research: methodological frontier and future directions,” Analytic Methods in Accident Research, vol. 1, pp. 1–22, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Huang, H. C. Chin, and M. Haque, “Empirical evaluation of alternative approaches in identifying crash hot spots,” Transportation Research Record, no. 2103, pp. 32–41, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. Q. Zeng and H. Huang, “Bayesian spatial joint modeling of traffic crashes on an urban road network,” Accident Analysis & Prevention, vol. 67, pp. 105–112, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. Q. Zeng, H. Wen, H. Huang, and M. Abdel-Aty, “A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments,” Accident Analysis & Prevention, vol. 100, pp. 37–43, 2017. View at Publisher · View at Google Scholar · View at Scopus
  10. S. Barua, K. El-Basyouny, and M. T. Islam, “Multivariate random parameters collision count data models with spatial heterogeneity,” Analytic Methods in Accident Research, vol. 9, pp. 1–15, 2016. View at Publisher · View at Google Scholar · View at Scopus
  11. M. Blangiardo and M. Cameletti, Spatial and spatio-temporal Bayesian models with R-INLA, John Wiley & Sons, Ltd., 2015. View at MathSciNet
  12. H. Huang and M. Abdel-Aty, “Multilevel data and Bayesian analysis in traffic safety,” Accident Analysis & Prevention, vol. 42, no. 6, pp. 1556–1565, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. S. P. Washington, M. G. Karlaftis, and F. L. Mannering, Statistical and Econometric Methods for Transportation Data Analysis, CRC Press, Boca Raton, Fla, USA, 2nd edition, 2011. View at MathSciNet
  14. X. Wang and M. Abdel-Aty, “Temporal and spatial analyses of rear-end crashes at signalized intersections,” Accident Analysis & Prevention, vol. 38, no. 6, pp. 1137–1150, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. W. Xuesong, M. Abdel-Aty, and P. A. Brady, “Crash estimation at signalized intersections: significant factors and temporal effect,” Transportation Research Record, no. 1953, pp. 10–20, 2006. View at Google Scholar · View at Scopus
  16. R. B. Noland, M. A. Quddus, and W. Y. Ochieng, “The effect of the London congestion charge on road casualties: An intervention analysis,” Transportation, vol. 35, no. 1, pp. 73–91, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. M. A. Quddus, “Time series count data models: an empirical application to traffic accidents,” Accident Analysis & Prevention, vol. 40, no. 5, pp. 1732–1741, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. M. Castro, R. Paleti, and C. R. Bhat, “A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections,” Transportation Research Part B: Methodological, vol. 46, no. 1, pp. 253–272, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. Y.-C. Chiou and C. Fu, “Modeling crash frequency and severity with spatiotemporal dependence,” Analytic Methods in Accident Research, vol. 5-6, pp. 43–58, 2015. View at Publisher · View at Google Scholar · View at Scopus
  20. S.-P. Miaou, “The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions,” Accident Analysis & Prevention, vol. 26, no. 4, pp. 471–482, 1994. View at Publisher · View at Google Scholar · View at Scopus
  21. P. Congdon, Applied Bayesian Modelling, John Wiley and Sons, 2nd edition, 2014. View at Publisher · View at Google Scholar · View at MathSciNet
  22. X. Xu, S. Xie, S. C. Wong, P. Xu, H. Huang, and X. Pei, “Severity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model,” Journal of Advanced Transportation, vol. 50, no. 8, pp. 2015–2028, 2016. View at Publisher · View at Google Scholar · View at Scopus
  23. D. J. Spiegelhalter, N. G. Best, B. P. Carlin, and A. van der Linde, “Bayesian measures of model complexity and fit,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 64, no. 4, pp. 583–639, 2002. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. D. J. Spiegelhalter, A. Thomas, N. G. Best, and D. Lunn, “WinBUGS user manual,” MRC Biostatistics Unit, 2005. View at Google Scholar
  25. Q. Zeng, H. Wen, H. Huang, X. Pei, and S. Wong, “A multivariate random-parameters Tobit model for analyzing highway crash rates by injury severity,” Accident Analysis & Prevention, vol. 99, pp. 184–191, 2017. View at Publisher · View at Google Scholar
  26. J. Aguero-Valverde, “Full Bayes Poisson gamma, Poisson lognormal, and zero inflated random effects models: comparing the precision of crash frequency estimates,” Accident Analysis & Prevention, vol. 50, pp. 289–297, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. Q. Zeng, H. Huang, X. Pei, S. C. Wong, and M. Gao, “Rule extraction from an optimized neural network for traffic crash frequency modeling,” Accident Analysis & Prevention, vol. 97, pp. 87–95, 2016. View at Publisher · View at Google Scholar · View at Scopus
  28. S. Labi, “Efficacies of roadway safety improvements across functional subclasses of rural two-lane highways,” Journal of Safety Research, vol. 42, no. 4, pp. 231–239, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. Y. Xie, D. Lord, and Y. Zhang, “Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis,” Accident Analysis & Prevention, vol. 39, no. 5, pp. 922–933, 2007. View at Publisher · View at Google Scholar · View at Scopus
  30. X. Qin, J. N. Ivan, and N. Ravishanker, “Selecting exposure measures in crash rate prediction for two-lane highway segments,” Accident Analysis & Prevention, vol. 36, no. 2, pp. 183–191, 2004. View at Publisher · View at Google Scholar · View at Scopus