An integrated clustering and Bayesian approach to investigate the severity of pedestrian collisions at highway-railway grade crossings collisions

References

• Anderson, T. K. (2009). Kernel density estimation and K-means clustering to profile road accident hotspots. Accident; Analysis and Prevention, 41(3), 359–364. doi:10.1016/j.aap.2008.12.014
   PubMed Web of Science ®Google Scholar
• Austin, R. D., & Carson, J. L. (2002). An alternative accident prediction model for highway-rail interfaces. Accident; Analysis and Prevention, 34(1), 31–42.
   PubMed Web of Science ®Google Scholar
• El-Basyouny, K., & Sayed, T. (2009). Collision prediction models using multivariate Poisson-lognormal regression. Accident; Analysis and Prevention, 41(4), 820–828.
   PubMed Web of Science ®Google Scholar
• Eluru, N., Bagheri, M., Miranda-Moreno, L. F., & Fu, L. (2012). A latent class modeling approach for identifying vehicle driver injury severity factors at highway-railway crossings. Accident; Analysis and Prevention, 47, 119–127.
   PubMed Web of Science ®Google Scholar
• Eluru, N., Bagheri, M., Miranda-Moreno, L. F., & Fu, L. (2012). A latent class modelling approach for identifying vehicle driver injury severity factors at highway-railway crossings. Accident Analysis & Prevention, 47, 119–127. doi:10.1016/j.aap.2012.01.027
   PubMed Web of Science ®Google Scholar
• Eluru, N., Bagheri, M., Miranda-Moreno, L. F., & Fu, L. (2012). A latent class modelling approach for identifying vehicle driver injury severity factors at highway-railway crossings. Accident Analysis and Prevention, 48, 119–127.
   Google Scholar
• Fan, W., Kane, M., & Haile, E. (2015). Predicting the severity of pedestrian crashes on highway–rail grade crossings. Advances in Transportation Studies an International Journal Section A, 36, 63–74.
   Google Scholar
• Federal Railroad Administration (FRA). (2020a). Office of safety analysis. Retrieved from https://safetydata.fra.dot.gov/OfficeofSafety/Default.aspx
   Google Scholar
• Federal Railroad Administration (FRA). (2020b). Retrieved from https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx
   Google Scholar
• Freeman, J., McMaster, M., & Rakotonirainy, A. (2015). An exploration into younger and older pedestrians’ risky behaviours at train level crossings. Safety, 1(1), 16–27. doi:10.3390/safety1010016
   Web of Science ®Google Scholar
• Ghomi, H., Bagheri, M., Fu, L., & Miranda-Moreno, L. F. (2016). Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study. Traffic Injury Prevention, 17(8), 833–841. doi:10.1080/15389588.2016.1151011
   PubMed Web of Science ®Google Scholar
• Ghomi, H., & Hussein, M. (2021). An integrated clustering and copula-based model to assess the impact of intersection characteristics on violation-related collisions. Accident; Analysis and Prevention, 159, 106283.
   PubMed Web of Science ®Google Scholar
• Gormley, T. A., & Matsa, D. A. (2014). How to (and not to) control for unobserved heterogeneity. Review of Financial Studies, 27(2), 617–661. doi:10.1093/rfs/hht047
   Web of Science ®Google Scholar
• Hagenaars, J. A., & McCutcheon, A. (2002). Applied latent class analysis, methodology. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis. London: Pearson Education Limited.
   Google Scholar
• Haleem, K., & Gan, A. (2015). Contributing factors of crash injury severity at public highway-railroad grade crossings in the U.S. Journal of Safety Research, 53, 23–29.
   PubMed Web of Science ®Google Scholar
• Hao, W., & Daniel, J. (2013). Motor vehicle driver injury severity study at highway-rail grade crossings in the United States. Transportation Research Board, 51, 41–48.
   Google Scholar
• Hussein, M., Sayed, T., El-Basyouny, K., & Leur, P. d. (2020). Investigating safety effects of wider longitudinal pavement markings. Accident; Analysis and Prevention, 142, 105527.
   PubMed Web of Science ®Google Scholar
• Kang, Y., & Khattak, A. (2017). A cluster based approach to analyze crash injury severity at highway-rail grade crossings. Transportation Research Record: Journal of the Transportation Research Board, 2608(1), 58–69. doi:10.3141/2608-07
   Google Scholar
• Kaplan, S., & Prato, C. G. (2013). Cyclist-motorist crash patterns in Denmark: A latent class clustering approach. Traffic Injury Prevention, 14(7), 725–733.
   PubMed Web of Science ®Google Scholar
• Kemalbay, G., & Korkmazoğlu, O. B. (2014). Categorical principal component logistic regression: A case study for housing loan approval. Social and Behavioral Sciences, 109, 730–736.
   Google Scholar
• Khattak, A. (2013). Severity of pedestrian crashes at highway-rail grade crossings. Proceedings of the 92nd Annual Meeting of the Transportation Research Board.
   Google Scholar
• Khattak, A., & Luo, Z. (2011). Pedestrian and bicyclist violations at highway-rail grade crossings. Transportation Research Record: Journal of the Transportation Research Board, 2250(1), 76–82.
   Google Scholar
• Kim, J. S., & Kim, B. S. (2018). Analysis of fire-accident factors using big-data analysis method for construction areas. KSCE Journal of Civil Engineering, 22(5), 1535–1543. doi:10.1007/s12205-017-0767-7
   Web of Science ®Google Scholar
• Lenne, M. G., Rudin-Brown, C. M., Navarro, J., Edquist, J., Trotter, M., & Tomasevic, N. (2011). Driver behaviour at rail level crossings: Responses to flashing lights, traffic signals and stop signs in simulated rural driving. Applied Ergonomics, 42(4), 548–554. doi:10.1016/j.apergo.2010.08.011
   PubMed Web of Science ®Google Scholar
• Lerer, L. B., & Matzopoulos, R. (1996). Meeting the challenge of railway injury in a South African city. The Lancet, 348(9028), 664–667. doi:10.1016/S0140-6736(96)02100-9
   PubMed Web of Science ®Google Scholar
• Li, W., Carriquiry, A., Pawlovich, M., & Welch, T. (2008). The choice of statistical models in road safety countermeasure effectiveness studies in Iowa. Accident; Analysis and Prevention, 40(4), 1531–1542.
   PubMed Web of Science ®Google Scholar
• Liu, J., Khattak, A. J., Richards, S. H., & Nambisan, S. (2015). What are the differences in driver injury outcomes at highway-rail grade crossings?: Untangling the role of pre-crash behaviors. Accident; Analysis and Prevention, 85, 157–169.
   PubMed Web of Science ®Google Scholar
• Lobb, B., Harre, N., & Suddendorf, T. H. (2001). An evaluation of a suburban railway pedestrian crossing safety programme. Accident; Analysis and Prevention, 33(2), 157–165. doi:10.1016/S0001-4575(00)00026-9
   PubMed Web of Science ®Google Scholar
• Maji, A., Velaga, N. R., & Urie, Y. (2018). Hierarchical clustering analysis framework of mutually exclusive crash causation parameters for regional road safety strategies. International Journal of Injury Control and Safety Promotion, 25(3), 257–271.
   PubMed Web of Science ®Google Scholar
• McCollister, G. M., & Pflaum, C. A. (2007). Model to predict the probability of highway rail crossing accidents. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 221(3), 321–329. doi:10.1243/09544097JRRT84
   Web of Science ®Google Scholar
• Metaxatos, P., & Sriraj, P. S. (2013). Transportation Research Board 92nd Annual Meeting, TRID, Washington DC, United States, 13–17 January.
   Google Scholar
• Metaxatos, P., & Sriraj, P. S. (2015). Pedestrian safety at rail grade crossings: Focus areas for research and intervention. Urban Rail Transit, 1(4), 238–248. doi:10.1007/s40864-016-0030-4
   Web of Science ®Google Scholar
• Mohamed, M. G., Saunier, N., Miranda-Moreno, L. F., & Ukkusuri, S. V. (2013). A clustering regression approach: A comprehensive injury severity analysis of pedestrian-vehicle crashes in New York, US and Montreal, Canada. Safety Science, 54, 27–37. doi:10.1016/j.ssci.2012.11.001
   Web of Science ®Google Scholar
• Mohanty, M. K., Panigrahi, M. K., Mohanty, S., & Patnaik, K. K. (2007). Death due to traumatic railway injury. Medicine, Science and the Law, 47(2), 156–160. doi:10.1258/rsmmsl.47.2.156
   PubMed Web of Science ®Google Scholar
• Moore, D. S., Notz, W. I., & Flinger, M. A. (2013). The basic practice of statistics (6th ed.). New York: Macmillan Learning.
   Google Scholar
• Moore, T. J., Wilson, J. R., & Hartman, M. (1991). Train versus pedestrian accidents. Southern Medical Journal, 84(9), 1097–1102.
   PubMed Web of Science ®Google Scholar
• Nixon, J., Corcoran, A., Fielding, L., & Eastgate, J. (1985). Fatal and nonfatal accidents on the railways-a study of injuries to individuals, with particular reference to children and to nonfatal trauma. Accident; Analysis and Prevention, 17(3), 217–222. − doi:10.1016/0001-4575(85)90054-5
   PubMed Web of Science ®Google Scholar
• Oberski, D. (2016). Mixture models: Latent profile and latent class analysis. In J. Robertson, & M. Kaptein (Eds.), Modern statistical methods for HCI (pp. 275–287). Cham: Springer.
   Google Scholar
• Osama, A., & Sayed, T. (2017). Macro-spatial approach for evaluating the impact of socio-economics, land use, built environment and road facility on pedestrian safety. Canadian Journal of Civil Engineering, 44(12), 1036–1044. doi:10.1139/cjce-2017-0145
   Web of Science ®Google Scholar
• Park, Y. J., & Saccomanno, F. F. (2005). Evaluating factors affecting safety at highway–railway grade crossings. Transportation Research Record: Journal of the Transportation Research Board, 1918(1), 1–9. doi:10.1177/0361198105191800101
   Google Scholar
• Pelletier, A. (1997). Deaths among railroad trespassers. The role of alcohol in fatal injuries. JAMA, 277(13), 1064–1066. doi:10.1001/jama.277.13.1064
   PubMed Web of Science ®Google Scholar
• Porcu, M., & Giambona, F. (2016). Introduction to latent class analysis with applications. Journal of Early Adolescence, 37(1), 129–158.
   Web of Science ®Google Scholar
• Raub, R. A. (2009). Examination of highway-rail grade crossing collisions nationally from 1998 to 2007. Transportation Research Record: Journal of the Transportation Research Board, 2122(1), 63–71. doi:10.3141/2122-08
   Google Scholar
• Saccomanno, F. F., Fu, L., Ren, C., & Miranda-Moreno, L. F. (2003). Identifying highway\x{FFFE}railway grade crossing black spots: phase 1, Department of Civil Engineering, University of Waterloo.
   Google Scholar
• Saukani, N., & Ismail, N. A. (2019). Identifying the components of social capital by categorical principal component analysis (CATPCA). Social Indicators Research, 141(2), 631–655. doi:10.1007/s11205-018-1842-2
   Web of Science ®Google Scholar
• Savage, I. (2016). Analysis of Fatal Train-Pedestrian Collisions in Metropolitan Chicago 2004-2012. Accident; Analysis and Prevention, 86, 217–228.
   PubMed Web of Science ®Google Scholar
• Shirmohammadi, H., Hadadi, F., & Saeedian, M. (2019). Clustering Analysis of Drivers Based on Behavioral Characteristics Regarding Road Safety. International Journal of Civil Engineering, 17(8), 1327–1340. doi:10.1007/s40999-018-00390-2
   Web of Science ®Google Scholar
• Shu, X. (2020). Knowledge Discovery in the Social Sciences: A Data Mining Approach. Berkeley, CA: University of California Press.
   Google Scholar
• Silla, A., & Luoma, J. (2011). Effect of three countermeasures against the illegal crossing of railway tracks. Accident; Analysis and Prevention, 43(3), 1089–1094. doi:10.1016/j.aap.2010.12.017
   PubMed Web of Science ®Google Scholar
• Silla, A., & Luoma, J. (2012). Main characteristics of train-pedestrian fatalities on Finnish railroads. Accident; Analysis and Prevention, 45, 61–66. doi:10.1016/j.aap.2011.11.008
   PubMed Web of Science ®Google Scholar
• Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society B, 64, 1–34.
   Google Scholar
• Wang, X., Liu, J., Khattak, A. J., & Clarke, D. (2016). Non-crossing rail-trespassing crashes in the past decade: A spatial approach to analyzing injury severity. Safety Science, 82, 44–55. doi:10.1016/j.ssci.2015.08.017
   Web of Science ®Google Scholar
• Zhao, S., Iranitalab, A., & Khattak, A. J. (2019). A clustering approach to injury severity in pedestrian-train crashes at highway-rail grade crossings. Journal of Transportation Safety & Security, 11(3), 305–322. doi:10.1080/19439962.2018.1428257
   Web of Science ®Google Scholar
• Zhao, S., Iranitalab, A., & Khattak, A. J. (2016). Investigation of pedestrian injury severity in crashes at highway-rail grade crossings using latent class analysis. Transportation Research Board 95th Annual Meeting.
   Google Scholar