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Article

Investigation of factors contributing to bus-crash severity based on extended hierarchical ordered probit model with heteroscedasticity

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References

  • Barua, U., & Tay, R. (2010). Severity of urban transit bus crashes in Bangladesh. Journal of Advanced Transportation, 44(1), 34–41. doi:10.1002/atr.104
  • Chen, F., Song, M., & Ma, X. (2019). Investigation on the injury severity of drivers in rear-end collisions between cars using a random parameters bivariate ordered probit model. International Journal of Environmental Research and Public Health, 16, 2632. doi:10.3390/ijerph16142632
  • Chimba, D., Sando, T., & Kwigizile, V. (2010). Effect of bus size and operation to crash occurrences. Accident; Analysis and Prevention, 42(6), 2063–2067. doi:10.1016/j.aap.2010.06.018
  • Feng, S., Li, Z., Ci, Y., & Zhang, G. (2016). Risk factors affecting fatal bus accident severity: Their impact on different types of bus drivers. Accident; Analysis and Prevention, 86, 29–39. doi:10.1016/j.aap.2015.09.025
  • Fountas, G., & Anastasopoulos, P. C. (2017). A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities. Analytic Methods in Accident Research, 15, 1–16. doi:10.1016/j.amar.2017.03.002
  • Goh, K. C. K., Currie, G., Sarvi, M., & Logan, D. (2014). Bus accident analysis of routes with/without bus priority. Accident; Analysis and Prevention, 65, 18–27. doi:10.1016/j.aap.2013.12.002
  • Greene, W. H., & Hensher, D. A. (2010). Modeling ordered choices A primer. New York: Cambridge University Press.
  • Gu, X., Yan, X., Ma, L., & Liu, X. (2020). Modeling the service-route-based crash frequency by a spatiotemporal-random-effect zero-inflated negative binomial model: An empirical analysis for bus-involved crashes. Accident; Analysis and Prevention, 144, 105674. doi:10.1016/j.aap.2020.105674
  • Guo, Y., Sayed, T., & Zaki, M. H. (2020). Examining two-wheelers' overtaking behavior and lateral distance choices at a shared roadway facility. Journal of Transportation Safety & Security, 12(8), 1046–1066. doi:10.1080/19439962.2019.1571549
  • Han, W., & Zhao, J. (2020). Driver behaviour and traffic accident involvement among professional urban bus drivers in China. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 184–197. doi:10.1016/j.trf.2020.08.007
  • Kaplan, S., & Prato, C. G. (2012). Risk factors associated with bus accident severity in the United States: A generalized ordered logit model. Journal of Safety Research, 43(3), 171–180. doi:10.1016/j.jsr.2012.05.003
  • Kim, J., Ulfarsson, G. F., Shankar, V. N., & Kim, S. (2008). Age and pedestrian injury severity in motor-vehicle crashes: A heteroskedastic logit analysis. Accident; Analysis and Prevention, 40(5), 1695–1702. doi:10.1016/j.aap.2008.06.005
  • Lemp, J. D., Kockelman, K. M., & Unnikrishnan, A. (2011). Analysis of large truck crash severity using heteroskedastic ordered probit models. Accident; Analysis and Prevention, 43(1), 370–380. doi:10.1016/j.aap.2010.09.006
  • Mannering, F. L., & Bhat, C. R. (2014). Analytic methods in accident research: Methodological frontier and future directions. Analytic Methods in Accident Research, 1, 1–22. doi:10.1016/j.amar.2013.09.001
  • Mannering, F. L., Shankar, V., & Bhat, C. R. (2016). Unobserved heterogeneity and the statistical analysis of highway accident data. Analytic Methods in Accident Research, 11, 1–16. doi:10.1016/j.amar.2016.04.001
  • Meng, Q., Weng, J., & Qu, X. (2010). A probabilistic quantitative risk assessment model for the long-term work zone crashes. Accident; Analysis and Prevention, 42(6), 1866–1877. doi:10.1016/j.aap.2010.05.007
  • Nasri, M., & Aghabayk, K. (2020). Assessing risk factors associated with urban transit bus involved accident severity: A case study of a Middle East country. International Journal of Crashworthiness, 1–11. doi:10.1080/13588265.2020.1718465
  • Park, H., Joo, Y., Kho, S., Kim, D., & Park, B. (2019). Injury severity of bus–pedestrian crashes in South Korea considering the effects of regional and company factors. Sustainability, 11(11), 3169. doi:10.3390/su11113169
  • Prato, C. G., & Kaplan, S. (2014). Bus accident severity and passenger injury: Evidence from Denmark. European Transport Research Review, 6(1), 17–30. doi:10.1007/s12544-013-0107-z
  • Rahman, M., Kattan, L., & Tay, R. (2011). Injury risk in collisions involving buses in Alberta. Transportation Research Record: Journal of the Transportation Research Board, 2265(1), 13–26. doi:10.3141/2265-02
  • Raihan, M. A., Alluri, P., Wu, W., & Gan, A. (2019). Estimation of bicycle crash modification factors (CMFs) on urban facilities using zero inflated negative binomial models. Accident; Analysis and Prevention, 123, 303–313. doi:10.1016/j.aap.2018.12.009
  • Sam, E. F., Daniels, S., Brijs, K., Brijs, T., & Wets, G. (2018). Modelling public bus/minibus transport accident severity in Ghana. Accident; Analysis and Prevention, 119, 114–121. doi:10.1016/j.aap.2018.07.008
  • Savolainen, P. T., Mannering, F. L., Lord, D., & Quddus, M. A. (2011). The statistical analysis of highway crash-injury severities: A review and assessment of methodological alternatives. Accident; Analysis and Prevention, 43(5), 1666–1676. doi:10.1016/j.aap.2011.03.025
  • Shen, J., Wang, T., Zheng, C., & Yu, M. (2020). Determinants of bicyclist injury severity resulting from crashes at roundabouts, crossroads, and T-junctions. Journal of Advanced Transportation, 2020, 1–12.
  • Shirlee, L. (2019). Can public transportation reduce accidents? Evidence from the introduction of late-night buses in Israeli cities. Regional Science and Urban Economics, 74, 99–117.
  • Tamakloe, R., Hong, J., & Park, D. (2020). A copula-based approach for jointly modeling crash severity and number of vehicles involved in express bus crashes on expressways considering temporal stability of data. Accident; Analysis and Prevention, 146, 105736. doi:10.1016/j.aap.2020.105736
  • Wang, X., & Abdel-Aty, M. (2008). Analysis of left-turn crash injury severity by conflicting pattern using partial proportional odds models. Accident; Analysis and Prevention, 40(5), 1674–1682. doi:10.1016/j.aap.2008.06.001
  • Wang, X., & Kockelman, K. M. (2005). Use of heteroscedastic ordered logit model to study severity of occupant injury. Transportation Research Record: Journal of the Transportation Research Board, 1908(1), 195–204. doi:10.1177/0361198105190800124
  • Wang, X., Huang, K., & Yang, L. (2019). Effects of socio-demographic, personality and mental health factors on traffic violations in Chinese bus drivers. Psychology, Health & Medicine, 24(7), 890–900. doi:10.1080/13548506.2019.1567928
  • Wang, Y., & Prato, C. G. (2019). Determinants of injury severity for truck crashes on mountain expressways in China: A case-study with a partial proportional odds model. Safety Science, 117, 100–107. doi:10.1016/j.ssci.2019.04.011
  • Weng, J., & Meng, Q. (2012). Effects of environment, vehicle and driver characteristics on risky driving behavior at work zones. Safety Science, 50(4), 1034–1042. doi:10.1016/j.ssci.2011.12.005
  • Yan, X., Harb, R., & Radwan, E. (2008). Analyses of factors of crash avoidance maneuvers using the general estimates system. Traffic Injury Prevention, 9(2), 173–180. doi:10.1080/15389580701869356
  • Ye, F., & Lord, D. (2014). Comparing three commonly used crash severity models on sample size requirements: Multinomial logit, ordered probit and mixed logit models. Analytic Methods in Accident Research, 1, 72–85. doi:10.1016/j.amar.2013.03.001
  • Yoon, S., Kho, S., & Kim, D. (2017). Effect of regional characteristics on injury severity in local bus crashes. Transportation Research Record: Journal of the Transportation Research Board, 2647(1), 1–8. doi:10.3141/2647-01
  • Yu, M., Zheng, C., Ma, C., & Shen, J. (2020). The temporal stability of factors affecting driver injury severity in run-off-road crashes: A random parameters ordered probit model with heterogeneity in the means approach. Accident; Analysis and Prevention, 144, 105677. doi:10.1016/j.aap.2020.105677
  • Zeng, Q., Wang, X., Wen, H., & Yuan, Q. (2020). An empirical investigation of the factors contributing to local-vehicle and non-local-vehicle crashes on freeway. Journal of Transportation Safety & Security, 1–15. doi:10.1080/19439962.2020.1779422
  • Zhai, G., Yang, H., & Liu, J. (2020). Is the front passenger seat always the "death seat"? An application of a hierarchical ordered probit model for occupant injury severity. International Journal of Injury Control and Safety Promotion, 27(4), 438–446. doi:10.1080/17457300.2020.1810072
  • Zhang, Z., Yang, R., Yuan, Y., Blackwelder, G., & Yang, X. T. (2020). Examining driver injury severity in left-turn crashes using hierarchical ordered probit models. Traffic Injury Prevention, 22(1), 57–62. doi:10.1080/15389588.2020.1841899
  • Zou, X., Vu, H. L., & Huang, H. (2020). Fifty years of accident analysis & prevention: A bibliometric and scientometric overview. Accident Analysis and Prevention, 144, 105568. doi:10.1016/j.aap.2020.105568

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