Injury severity of single-vehicle large-truck crashes: accounting for heterogeneity

References

• Al-Bdairi, N. S. S., & Hernandez, S. (2017). An empirical analysis of run-off-road injury severity crashes involving large trucks. Accident; Analysis and Prevention, 102, 93–100. https://doi.org/10.1016/j.aap.2017.02.024
   PubMed Web of Science ®Google Scholar
• Al-Bdairi, N. S. S., & Hernandez, S. (2020). Comparison of contributing factors for injury severity of large truck drivers in run-off-road crashes on rural and urban roadways: Accounting for unobserved heterogeneity. International Journal of Transportation Science and Technology, 9(2), 116–127. https://doi.org/10.1016/j.ijtst.2020.01.004
   Google Scholar
• Al-Bdairi, N. S. S., Hernandez, S., & Anderson, J. (2018). Contributing factors to run-off-road crashes involving large trucks under lighted and dark conditions. Journal of Transportation Engineering, Part A: Systems, 144(1), 04017066. https://doi.org/10.1061/JTEPBS.0000104
   Web of Science ®Google Scholar
• Azimi, G., Rahimi, A., Asgari, H., & Jin, X. (2020). Severity analysis for large truck rollover crashes using a random parameter ordered logit model. Accident; Analysis and Prevention, 135(April 2019), 105355. https://doi.org/10.1016/j.aap.2019.105355
   PubMedGoogle Scholar
• Behnood, A., & Al-Bdairi, N. S. S. (2020). Determinant of injury severities in large truck crashes: A weekly instability analysis. Safety Science, 131(July), 104911. https://doi.org/10.1016/j.ssci.2020.104911
   Google Scholar
• Behnood, A., & Mannering, F. (2019). Time-of-day variations and temporal instability of factors affecting injury severities in large-truck crashes. Analytic Methods in Accident Research, 23, 100102. https://doi.org/10.1016/j.amar.2019.100102
   Web of Science ®Google Scholar
• Bejleri, I. (2014). Signal Four Analytics (Issue October). https://s4.geoplan.ufl.edu/
   Google Scholar
• Chang, L. Y., & Mannering, F. (1999). Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents. Accident; Analysis and Prevention, 31(5), 579–592. https://doi.org/10.1016/S0001-4575(99)00014-7
   PubMed Web of Science ®Google Scholar
• Dabbour, E., Haider, M., & Diaa, E. (2019). Using random-parameter and fixed-parameter ordered models to explore temporal stability in factors affecting drivers’ injury severity in single-vehicle collisions. Journal of Traffic and Transportation Engineering (English Edition), 6(2), 132–146. https://doi.org/10.1016/j.jtte.2018.04.002
   Google Scholar
• Dong, B., Ma, X., Chen, F., & Chen, S. (2018). Investigating the differences of single-vehicle and multivehicle accident probability using mixed logit model. Journal of Advanced Transportation, 2018, 1–9. https://doi.org/10.1155/2018/2702360
   Google Scholar
• Florida Department of Highway Safety and Motor Vehicles. (2019). Uniform Traffic Crash Report Manual (Issue July).
   Google Scholar
• FMCSA. (2020). Large truck and bus crash facts 2018. Federal Motor Carrier Safety Administration. https://www.fmcsa.dot.gov/safety/data-and-statistics/large-truck-and-bus-crash-facts-2018
   Google Scholar
• Hao, W., Kamga, C., Yang, X., Ma, J. Q., Thorson, E., Zhong, M., & Wu, C. (2016). Driver injury severity study for truck involved accidents at highway-rail grade crossings in the United States. Transportation Research Part F: Traffic Psychology and Behaviour, 43, 379–386. https://doi.org/10.1016/j.trf.2016.09.001
   Web of Science ®Google Scholar
• Haq, M. T., Zlatkovic, M., & Ksaibati, K. (2020). Investigating occupant injury severity of truck-involved crashes based on vehicle types on a mountainous freeway: A hierarchical Bayesian random intercept approach. Accident; Analysis and Prevention, 144(June), 105654. https://doi.org/10.1016/j.aap.2020.105654
   PubMedGoogle Scholar
• Haq, M. T., Zlatkovic, M., & Ksaibati, K. (2021). Assessment of commercial truck driver injury severity based on truck configuration along a mountainous roadway using hierarchical Bayesian random intercept approach. Accident; Analysis and Prevention, 162(June 2020), 106392. https://doi.org/10.1016/j.aap.2021.106392
   PubMedGoogle Scholar
• Hernández, S., & Anderson, J. (2017). Truck parking: an emerging safety hazard to highway users.
   Google Scholar
• Hickman, J. S., Hanowski, R. J., & Bocanegra, J. (2018). A synthetic approach to compare the large truck crash causation study and naturalistic driving data. Accident; Analysis and Prevention, 112(July 2017), 11–14. https://doi.org/10.1016/j.aap.2017.12.006
   PubMedGoogle Scholar
• Islam, M., Alnawmasi, N., & Mannering, F. (2020). Unobserved heterogeneity and temporal instability in the analysis of work-zone crash-injury severities. Analytic Methods in Accident Research, 28, 100130. https://doi.org/10.1016/j.amar.2020.100130
   Web of Science ®Google Scholar
• Islam, M., & Hernandez, S. (2013). Large truck-involved crashes: Exploratory injury severity analysis. Journal of Transportation Engineering, 139(6), 596–604. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000539
   Web of Science ®Google Scholar
• Islam, M., Hosseini, P., & Jalayer, M. (2022). An analysis of single-vehicle truck crashes on rural curved segments accounting for unobserved heterogeneity. Journal of Safety Research, 80, 148–159. https://doi.org/10.1016/j.jsr.2021.11.011
   PubMed Web of Science ®Google Scholar
• Islam, S., Jones, S. L., & Dye, D. (2014). Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama. Accident; Analysis and Prevention, 67, 148–158. https://doi.org/10.1016/j.aap.2014.02.014
   PubMed Web of Science ®Google Scholar
• Ivan, J. N., Pasupathy, R. K., & Ossenbruggen, P. J. (1999). Differences in causality factors for single and multi-vehicle crashes on two-lane roads. Accident; Analysis and Prevention, 31(6), 695–704. https://doi.org/10.1016/S0001-4575(99)00030-5
   PubMed Web of Science ®Google Scholar
• Jin, X., Asgari, H., Lee, M., Rahimi, A., Azimi, G., Bejleri, I., Hakim, N., Zhai, L., & Carrick, G. (2019). Large truck crash analysis for freight mobility and safety enhancement in Florida. https://doi.org/10.13140/RG.2.2.30216.57606
   Google Scholar
• Khoda Bakhshi, A., & Ahmed, M. M. (2021). Coping with endogeneity and unobserved heterogeneity in real-time clustering critical crash occurrences nested within weather and road surface conditions. International Journal of Injury Control and Safety Promotion, 28(2), 208–221. https://doi.org/10.1080/17457300.2021.1907595
   PubMed Web of Science ®Google Scholar
• Kramer, B. (1996). An ordered logit model for the evaluation of Dutch non-life insurance companies. De Economist, 144(1), 79–91. https://doi.org/10.1007/BF01680262
   Google Scholar
• Naik, B., Tung, L. W., Zhao, S., & Khattak, A. J. (2016). Weather impacts on single-vehicle truck crash injury severity. Journal of Safety Research, 58, 57–65. https://doi.org/10.1016/j.jsr.2016.06.005
   PubMed Web of Science ®Google Scholar
• National Safety Council. (2021). Large trucks – Injury facts. https://injuryfacts.nsc.org/motor-vehicle/road-users/large-trucks/
   Google Scholar
• NCSA. (2021). Traffic safety facts 2019: A compilation of motor vehicle crash data. National Highway Traffic Safety Administration.
   Google Scholar
• Osman, M., Paleti, R., Mishra, S., & Golias, M. M. (2016). Analysis of injury severity of large truck crashes in work zones. Accident; Analysis and Prevention, 97, 261–273. https://doi.org/10.1016/j.aap.2016.10.020
   PubMed Web of Science ®Google Scholar
• Pahukula, J., Hernandez, S., & Unnikrishnan, A. (2015). A time of day analysis of crashes involving large trucks in urban areas. Accident; Analysis and Prevention, 75, 155–163. https://doi.org/10.1016/j.aap.2014.11.021
   PubMed Web of Science ®Google Scholar
• Rahimi, A., Azimi, G., Asgari, H., & Jin, X. (2019). Clustering approach toward large truck Crash analysis. Transportation Research Record: Journal of the Transportation Research Board, 2673(8), 73–85. https://doi.org/10.1177/0361198119839347
   Web of Science ®Google Scholar
• Rahimi, E., Shamshiripour, A., Samimi, A., & Mohammadian, A. (2020). Investigating the injury severity of single-vehicle truck crashes in a developing country. Accident; Analysis and Prevention, 137(October 2019), 105444. https://doi.org/10.1016/j.aap.2020.105444
   PubMedGoogle Scholar
• Rezaei, H., Macioszek, E., Derakhshesh, P., Houshyar, H., Ghabouli, E., Bakhshi Lomer, A. R., Ghanbari, R., & Esmailzadeh, A. (2023). A spatial decision support system for modeling urban resilience to natural hazards. Sustainability, 15(11), 8777. https://doi.org/10.3390/su15118777
   Web of Science ®Google Scholar
• Saffarzadeh, M., Rezaei, H., & Majidi, M. Z. (2022). A pricing model for freeway tolls based on the share of mode shift, route shift, travel time change and users’ willingness to pay (Case study: Tehran_Saveh Freeway). Journal of Transportation Research, 19(3), 359–370. 20.1001.1.17353459.1401.19.3.21.6
   Google Scholar
• Saha, P., Mashhadi, M. M. R., & Ksaibati, K. (2019). Impact of traffic citations to reduce truck crashes on challenging roadway geometry. International Journal of Injury Control and Safety Promotion, 26(1), 60–71. https://doi.org/10.1080/17457300.2018.1476386
   PubMed Web of Science ®Google Scholar
• Sarker, M. A. A., Rahimi, A., Azimi, G., & Jin, X. (2022). Investigating older adults’ propensity toward ridesourcing services. Journal of Transportation Engineering, Part A: Systems, 148(9), 1–11. https://doi.org/10.1061/JTEPBS.0000715
   Web of Science ®Google Scholar
• Song, L., & Fan, W. (2020). Combined latent class and partial proportional odds model approach to exploring the heterogeneities in truck-involved severities at cross and T-intersections. Accident; Analysis and Prevention, 144(February), 105638. https://doi.org/10.1016/j.aap.2020.105638
   PubMedGoogle Scholar
• Sprung, M., Chambers, M., & Smith-Pickel, S. (2018). Transportation Statistics Annual Report 2018. Bureau of Transportation Statistics, Preliminary Annual Report 2018. https://doi.org/10.21949/1502596
   Google Scholar
• Teoh, E. R., Carter, D. L., Smith, S., & McCartt, A. T. (2017). Crash risk factors for interstate large trucks in North Carolina. Journal of Safety Research, 62, 13–21. https://doi.org/10.1016/j.jsr.2017.05.002
   PubMed Web of Science ®Google Scholar
• Titiloye, I., Sarker, M. A. A., Jin, X., & Watts, B. (2023). Examining channel choice preferences for grocery shopping during the Covid-19 pandemic. International Journal of Transportation Science and Technology. Advance online publication. https://doi.org/10.1016/j.ijtst.2023.03.006
   Google Scholar
• Uddin, M., & Huynh, N. (2017). Truck-involved crashes injury severity analysis for different lighting conditions on rural and urban roadways. Accident; Analysis and Prevention, 108(September), 44–55. https://doi.org/10.1016/j.aap.2017.08.009
   PubMedGoogle Scholar
• Uddin, M., & Huynh, N. (2020). Injury severity analysis of truck-involved crashes under different weather conditions. Accident; Analysis and Prevention, 141(April), 105529. https://doi.org/10.1016/j.aap.2020.105529
   PubMedGoogle Scholar
• Ulfarsson, G. F., & Mannering, F. L. (2004). Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. Accident; Analysis and Prevention, 36(2), 135–147. https://doi.org/10.1016/S0001-4575(02)00135-5
   PubMed Web of Science ®Google Scholar
• Washington, S. P., Karlaftis, M. G., & Mannering, F. L. (2011). Statistical and econometric methods for transportation data analysis (2nd ed.). Taylor and Francis Group, LLC.
   Google Scholar
• Wu, Q., Chen, F., Zhang, G., Liu, X. C., Wang, H., & Bogus, S. M. (2014). Mixed logit model-based driver injury severity investigations in single- and multi-vehicle crashes on rural two-lane highways. Accident; Analysis and Prevention, 72, 105–115. https://doi.org/10.1016/j.aap.2014.06.014
   PubMed Web of Science ®Google Scholar
• Yuan, Y., Yang, M., Guo, Y., Rasouli, S., Gan, Z., & Ren, Y. (2021). Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers. Journal of Safety Research, 76, 154–165. https://doi.org/10.1016/j.jsr.2020.12.012
   PubMed Web of Science ®Google Scholar
• Zheng, Z., Lu, P., & Lantz, B. (2018). Commercial truck crash injury severity analysis using gradient boosting data mining model. Journal of Safety Research, 65, 115–124. https://doi.org/10.1016/j.jsr.2018.03.002
   PubMed Web of Science ®Google Scholar
• Zhu, X., & Srinivasan, S. (2011). A comprehensive analysis of factors influencing the injury severity of large-truck crashes. Accident; Analysis and Prevention, 43(1), 49–57. https://doi.org/10.1016/j.aap.2010.07.007
   PubMed Web of Science ®Google Scholar