Assessment of Fatal Rear-End Crash Risk Factors of an Expressway in India: A Random Parameter NB Modeling Approach
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 1
Abstract
This study aimed to identify the segment-specific risk factors for rear-end crashes on an expressway in India. The fatal crash data were analyzed from August 2012 to October 2018 with road geometry details, speed, volume, and roadside data. Negative binomial (NB) models with a random parameter framework accounted for the unobserved heterogeneity across the segments. A NB model with fixed parameters (FPNB) was used as a base model against basic random parameter NB (RPNB) and correlated random parameter NB (CRPNB) models. The results indicated that rear-end crashes comprised 49% of the total fatal crashes. Truck and car occupants constituted the highest share of victims in rear-end crashes. As per the estimate of log-likelihood for the developed models, CRPNB was best. The results of the RPNB model suggested that speed, Annual Average Daily Traffic (AADT), horizontal alignment radius, and vertical curve length were the significant variables. In the case of the CRPNB model, speed, AADT, and vertical curve length were the significant variables. Segments where a village was present along the expressway were comparatively safer. Segments where entry and exit ramps and underpasses were present and segments with hazards had higher chances of being associated with rear-end crashes. The study’s findings provide valuable insights into proposing interventions for reducing rear-end crashes on expressways in heterogeneous traffic conditions. Detailed investigations with additional data are required at segments with entry-exit ramps and horizontal and vertical curves. To sum up, the findings of this study may assist highway agencies and design engineers in designing new or evaluating existing expressways from a safety viewpoint.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
AASHTO. 2010. Highway safety manual 2010. Washington, DC: AASHTO.
Abdel-Aty, M. 2003. “Analysis of driver injury severity levels at multiple locations using ordered probit models.” J. Saf. Res. 34 (5): 597–603. https://doi.org/10.1016/j.jsr.2003.05.009.
Abdel-Aty, M., and H. Abdelwahab. 2004. “Modeling rear-end collisions including the role of driver’s visibility and light truck vehicles using a nested logit structure.” Accid. Anal. Prev. 36 (3): 447–456. https://doi.org/10.1016/S0001-4575(03)00040-X.
Alnawmasi, N., and F. Mannering. 2022. “A temporal assessment of distracted driving injury severities using alternate unobserved-heterogeneity modeling approaches.” Anal. Methods Accid. Res. 34 (Jun): 100216. https://doi.org/10.1016/j.amar.2022.100216.
Anastasopoulos, P. C., and F. L. Mannering. 2009. “A note on modeling vehicle accident frequencies with random-parameters count models.” Accid. Anal. Prev. 41 (1): 153–159. https://doi.org/10.1016/j.aap.2008.10.005.
Anastasopoulos, P. C., and F. L. Mannering. 2011. “An empirical assessment of fixed and random parameter logit models using crash- and non-crash-specific injury data.” Accid. Anal. Prev. 43 (3): 1140–1147. https://doi.org/10.1016/j.aap.2010.12.024.
Azimi, G., A. Rahimi, H. Asgari, and X. Jin. 2022. “Injury severity analysis for large truck-involved crashes: Accounting for heterogeneity.” Transp. Res. Rec. 03611981221091562. https://doi.org/10.1177/03611981221091562.
Barua, S., K. El-Basyouny, and M. T. Islam. 2016. “Multivariate random parameters collision count data models with spatial heterogeneity.” Anal. Methods Accid. Res. 9 (Mar): 1–15. https://doi.org/10.1016/j.amar.2015.11.002.
Behnood, A., and N. S. S. Al-Bdairi. 2020. “Determinant of injury severities in large truck crashes: A weekly instability analysis.” Saf. Sci. 131 (Jul): 104911. https://doi.org/10.1016/j.ssci.2020.104911.
Bhalla, K., N. Khurana, D. Bose, K. V. Navaratne, G. Tiwari, and D. Mohan. 2017. “Official government statistics of road traffic deaths in India under-represent pedestrians and motorized two wheeler riders.” Inj. Prev. 23 (1): 1–7. https://doi.org/10.1136/injuryprev-2016-042053.
Bhalla, K., D. Mohan, and B. O’Neill. 2020a. “How much would low- and middle-income countries benefit from addressing the key risk factors of road traffic injuries?” Int. J. Inj. Control Saf. Promot. 27 (1): 83–90. https://doi.org/10.1080/17457300.2019.1708411.
Bhalla, K., D. Mohan, and B. O’Neill. 2020b. “What can we learn from the historic road safety performance of high-income countries?” Int. J. Inj. Control Saf. Promot. 27 (1): 27–34. https://doi.org/10.1080/17457300.2019.1704789.
Bhat, C. R. 2003. “Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences.” Transp. Res. Part B Methodol. 37 (9): 837–855. https://doi.org/10.1016/S0191-2615(02)00090-5.
Buddhavarapu, P., J. G. Scott, and J. A. Prozzi. 2016. “Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data.” Transp. Res. Part B Methodol. 91 (Jan): 492–510. https://doi.org/10.1016/j.trb.2016.06.005.
Castro, M. Í., J. F. Sánchez, J. A. Sánchez, and L. Iglesias. 2011. “Operating speed and speed differential for highway design consistency.” J. Transp. Eng. 137 (11): 837–840. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000309.
Chatterjee, S., and S. Mitra. 2019. “Safety assessment of two-lane highway using a combined proactive and reactive approach: Case study from Indian national highways.” Transp. Res. Rec. 2673 (7): 709–721. https://doi.org/10.1177/0361198119846479.
Chikkakrishna, N. K., M. Parida, and S. S. Jain. 2016. “Identifying safety factors associated with crash frequency and severity on nonurban four-lane highway stretch in India.” J. Transp. Saf. Secur. 9 (May): 6–32. https://doi.org/10.1080/19439962.2016.1150927.
Conway, K. S., and T. J. Kniesner. 1991. “The important econometric features of a linear regression model with cross-correlated random coefficients.” Econ. Lett. 35 (2): 143–147. https://doi.org/10.1016/0165-1765(91)90161-D.
Coruh, E., A. Bilgic, and A. Tortum. 2015. “Accident analysis with the random parameters negative binomial panel count data model.” Anal. Methods Accid. Res. 7 (Mar): 37–49. https://doi.org/10.1016/j.amar.2015.07.001.
Dandona, L., et al. 2017. “Nations within a nation: Variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study.” Lancet 390 (10111): 2437–2460. https://doi.org/10.1016/S0140-6736(17)32804-0.
Dandona, R., et al. 2020. “Mortality due to road injuries in the states of India: The Global Burden of Disease Study 1990–2017.” Lancet Public Health 5 (2): e86–e98. https://doi.org/10.1016/S2468-2667(19)30246-4.
Dandona, R., G. A. Kumar, M. A. Ameer, G. B. Reddy, and L. Dandona. 2008. “Under-reporting of road traffic injuries to the police: Results from two data sources in urban India.” Inj. Prev. 14 (6): 360–365. https://doi.org/10.1136/ip.2008.019638.
Dey, P. P., S. Chandra, and S. Gangopadhaya. 2006. “Speed distribution curves under mixed traffic conditions.” J. Transp. Eng. 132 (6): 475–481. https://doi.org/10.1061/(ASCE)0733-947X(2006)132:6(475).
Dhibi, M. 2019. “Road safety determinants in low and middle income countries.” Int. J. Inj. Control Saf. Promot. 26 (1): 99–107. https://doi.org/10.1080/17457300.2018.1482926.
Dinu, R. R., and A. Veeraragavan. 2011. “Random parameter models for accident prediction on two-lane undivided highways in India.” J. Saf. Res. 42 (1): 39–42. https://doi.org/10.1016/j.jsr.2010.11.007.
Elvik, R. 2004. “To what extent can theory account for the findings of road safety evaluation studies?” Accid. Anal. Prev. 36 (5): 841–849. https://doi.org/10.1016/j.aap.2003.08.003.
Fountas, G., and P. C. Anastasopoulos. 2017. “A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities.” Anal. Methods Accid. Res. 15 (Apr): 1–16. https://doi.org/10.1016/j.amar.2017.03.002.
Gitelman, V., E. Doveh, R. Carmel, and S. Hakkert. 2019. “The influence of shoulder characteristics on the safety level of two-lane roads: A case-study.” Accid. Anal. Prev. 122 (Oct): 108–118. https://doi.org/10.1016/j.aap.2018.10.003.
Greene, W. 2008. “Functional forms for the negative binomial model for count data.” Econ. Lett. 99 (3): 585–590. https://doi.org/10.1016/j.econlet.2007.10.015.
Greene, W. H. 2003. Econometric analysis. Parkside, SA, Australia: Pearson Education.
Greene, W. H. 2012. “Nlogit.” In Vol. 11 of Student reference guide. Plainview, NY: Econometric Software, Inc.
Gross, F., and E. T. Donnell. 2011. “Case-control and cross-sectional methods for estimating crash modification factors: Comparisons from roadway lighting and lane and shoulder width safety effect studies.” J. Saf. Res. 42 (2): 117–129. https://doi.org/10.1016/j.jsr.2011.03.003.
Gupta, M., and S. Bandyopadhyay. 2020. “Regulatory and road engineering interventions for preventing road traffic injuries and fatalities among vulnerable road users in low- and middle-income countries: A systematic review.” Front. Sustainable Cities 2 (May): 1–26. https://doi.org/10.3389/frsc.2020.00010.
Hauer, E. 2004a. “The harm done by tests of significance.” Accid. Anal. Prev. 36 (3): 495–500. https://doi.org/10.1016/S0001-4575(03)00036-8.
Hauer, E. 2004b. “Statistical road safety modeling.” Transp. Res. Rec. 1897 (1): 81–87. https://doi.org/10.3141/1897-11.
Hauer, E. 2009. “Speed and safety.” Transp. Res. Rec. 2103 (1): 10–17. https://doi.org/10.3141/2103-02.
Hong, J., J. Park, G. Lee, and D. Park. 2019. “Endogenous commercial driver’s traffic violations and freight truck-involved crashes on mainlines of expressway.” Accid. Anal. Prev. 131 (Jun): 327–335. https://doi.org/10.1016/j.aap.2019.07.026.
Hosseinzadeh, A., A. Moeinaddini, and A. Ghasemzadeh. 2021. “Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model.” J. Saf. Res. 77 (Jun): 151–160. https://doi.org/10.1016/j.jsr.2021.02.012.
Hou, Q., X. Huo, A. P. Tarko, and J. Leng. 2021. “Comparative analysis of alternative random parameters count data models in highway safety.” Anal. Methods Accid. Res. 30 (Apr): 100158. https://doi.org/10.1016/j.amar.2021.100158.
Hou, Q., A. P. Tarko, and X. Meng. 2018. “Investigating factors of crash frequency with random effects and random parameters models: New insights from Chinese freeway study.” Accid. Anal. Prev. 120 (Jan): 1–12. https://doi.org/10.1016/j.aap.2018.07.010.
Hsiao, M., A. Malhotra, J. S. Thakur, J. K. Sheth, A. B. Nathens, N. Dhingra, and P. Jha. 2013. “Road traffic injury mortality and its mechanisms in India: Nationally representative mortality survey of 1.1 million homes.” BMJ Open 3 (8): e002621. https://doi.org/10.1136/bmjopen-2013-002621.
Huo, X., J. Leng, Q. Hou, and H. Yang. 2020. “A correlated random parameters model with heterogeneity in means to account for unobserved heterogeneity in crash frequency analysis.” Transp. Res. Rec. 2674 (7): 312–322. https://doi.org/10.1177/0361198120922212.
ICMR, PHFI, and IHME (Indian Council of Medical Research, Public Health Foundation of India, and Institute for Health Metrics and Evaluation). 2017. India: Health of the Nation’s states the India state-level disease burden initiative. New Delhi, India: Government of India.
IRC (Indian Roads Congress). 2013. Manual of specifications and standards for expressways. IRC:SP:99-2013. New Delhi, India: IRC.
Islam, M., P. Hosseini, and M. Jalayer. 2022. “An analysis of single-vehicle truck crashes on rural curved segments accounting for unobserved heterogeneity.” J. Saf. Res. 80 (Apr): 148–159. https://doi.org/10.1016/j.jsr.2021.11.011.
Jovanis, P. P., S. Park, and K. Chen. 2005. “On the relationship of crash risk and driver hours of service.” In Proc., 2005 Int. Truck and Bus Safety and Security Symp. Alexandria, VA: National Safety Council.
Kabir, R., S. M. Remias, S. M. Lavrenz, and J. Waddell. 2021. “Assessing the impact of traffic signal performance on crash frequency for signalized intersections along urban arterials: A random parameter modeling approach.” Accid. Anal. Prev. 149 (Oct): 105868. https://doi.org/10.1016/j.aap.2020.105868.
Katiyar, P. 2019. “Why the Yamuna expressway continues to remain accident-prone.” Accessed July 14, 2019. https://economictimes.indiatimes.com/defaultinterstitial.cms.
Khan, M., A. Abdel-Rahim, and C. J. Williams. 2015. “Potential crash reduction benefits of shoulder rumble strips in two-lane rural highways.” Accid. Anal. Prev. 75 (Jul): 35–42. https://doi.org/10.1016/j.aap.2014.11.007.
Liu, P., and W. Fan. 2020. “Analyzing injury severity of rear-end crashes involving large trucks using a mixed logit model: A case study in North Carolina.” J. Transp. Saf. Secur. 2020 (5): 1–14. https://doi.org/10.1080/19439962.2020.1812784.
Lord, D., and F. Mannering. 2010. “The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives.” Transp. Res. Part A Policy Pract. 44 (5): 291–305.
Lord, D., and L. F. Miranda-Moreno. 2008. “Effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter of Poisson-gamma models for modeling motor vehicle crashes: A Bayesian perspective.” Saf. Sci. 46 (5): 751–770. https://doi.org/10.1016/j.ssci.2007.03.005.
Mannering, F. L., and C. R. Bhat. 2014. “Analytic methods in accident research: Methodological frontier and future directions.” Anal. Methods Accid. Res. 1 (Jan): 1–22. https://doi.org/10.1016/j.amar.2013.09.001.
Mannering, F. L., V. Shankar, and C. R. Bhat. 2016. “Unobserved heterogeneity and the statistical analysis of highway accident data.” Anal. Methods Accid. Res. 11 (Sep): 1–16. https://doi.org/10.1016/j.amar.2016.04.001.
Miaou, S. P., and D. Lord. 2003. “Modeling traffic crash-flow relationships for intersections: Dispersion parameter, functional form, and Bayes versus empirical Bayes methods.” Transp. Res. Rec. 1840 (1): 31–40. https://doi.org/10.3141/1840-04.
Miaou, S. P., and H. Lum. 1993. “Modeling vehicle accidents and highway geometric design relationships.” Accid. Anal. Prev. 25 (6): 689–709. https://doi.org/10.1016/0001-4575(93)90034-T.
Mitra, S., M. Haque, and M. J. King. 2017. “Effects of access, geometric design, and heterogeneous traffic on safety performance of divided multilane highways in India.” Supplement, J. Transp. Saf. Secur. 9 (S1): 216–235. https://doi.org/10.1080/19439962.2016.1237600.
Mitra, S., and S. Washington. 2012. “On the significance of omitted variables in intersection crash modeling.” Accid. Anal. Prev. 49 (Nov): 439–448. https://doi.org/10.1016/j.aap.2012.03.014.
Mizuno, K., D. Ojiro, T. Tanaka, S. Minusa, H. Kuriyama, E. Yamano, H. Kuratsune, and Y. Watanabe. 2020. “Relationship between truck driver fatigue and rear-end collision risk.” PLoS One 15 (9): e0238738. https://doi.org/10.1371/journal.pone.0238738.
Mohan, D., G. Tiwari, and K. Bhalla. 2017. Road safety in India: Status report 2016. New Delhi, India: Transportation Research and Injury Prevention Programme.
Mohan, D., G. Tiwari, M. Varghese, K. Bhalla, D. John, A. Saran, and H. White. 2020. “PROTOCOL: Effectiveness of road safety interventions: An evidence and gap map.” Campbell Syst. Rev. 16 (1): e1077. https://doi.org/10.1002/cl2.1077.
MoRTH. 2021a. “Bharatmala Phase-I | Ministry of Road Transport & Highways, Government of India.” Accessed October 21, 2021. https://nhai.gov.in/#/bharatmala-pariyojana.
MoRTH. 2021b. Road transport year book (2017-18 & 2018-19). New Delhi, India: MoRTH.
MoRTH. 2022. Road accidents in India 2020. New Delhi, India: MoRTH.
Naqvi, H. M., and G. Tiwari. 2015. “Accident analysis of a two-lane national highway in India.” SAE Tech. Paper 26 (162): 5. https://doi.org/10.4271/2015-26-0162.
NHAI (National Highways Development Project). 2021. “National highways development project.” Accessed October 21, 2021. https://nhai.gov.in/#/about-nhdp.
Park, M., and D. Lee. 2021. “A random parameter negative binomial model for signalized intersection accidents in Seoul, Korea.” Int. J. Inj. Control Saf. Promot. 28 (2): 201–207. https://doi.org/10.1080/17457300.2021.1907594.
Peeta, S., P. Zhang, and W. Zhou. 2005. “Behavior-based analysis of freeway car-truck interactions and related mitigation strategies.” Transp. Res. Part B Methodol. 39 (5): 417–451. https://doi.org/10.1016/j.trb.2004.06.002.
Qi, Y., R. Srinivasan, H. Teng, and R. Baker. 2013. “Analysis of the frequency and severity of rear-end crashes in work zones.” Traffic Inj. Prev. 14 (1): 61–72. https://doi.org/10.1080/15389588.2012.675109.
Russo, B. J., P. T. Savolainen, W. H. Schneider IV, and P. C. Anastasopoulos. 2014. “Comparison of factors affecting injury severity in angle collisions by fault status using a random parameters bivariate ordered probit model.” Anal. Methods Accid. Res. 2 (Jul): 21–29. https://doi.org/10.1016/j.amar.2014.03.001.
Saeed, T. U., T. Hall, H. Baroud, and M. J. Volovski. 2019. “Analyzing road crash frequencies with uncorrelated and correlated random-parameters count models: An empirical assessment of multilane highways.” Anal. Methods Accid. Res. 23 (Jun): 100101. https://doi.org/10.1016/j.amar.2019.100101.
Savolainen, P. T., F. L. Mannering, D. Lord, and M. A. Quddus. 2011. “The statistical analysis of highway crash-injury severities: A review and assessment of methodological alternatives.” Accid. Anal. Prev. 43 (5): 1666–1676. https://doi.org/10.1016/j.aap.2011.03.025.
Shao, X., X. Ma, F. Chen, M. Song, X. Pan, and K. You. 2020. “A random parameters ordered probit analysis of injury severity in truck involved rear-end collisions.” Int. J. Environ. Res. Public Health 17 (2): 395. https://doi.org/10.3390/ijerph17020395.
Shinar, D. 2017. “Crash countermeasures and design of safety.” In Traffic safety and human behavior, 1085–1175. Bingley, UK: Emerald Publishing. https://doi.org/10.1108/978-1-78635-221-720162019.
Shirazi, M., and D. Lord. 2021. “Use/analysis of crash data and underreporting of crash data.” In International encyclopedia of transportation, 726–730. Amsterdam, Netherlands: Elsevier. https://doi.org/10.1016/B978-0-08-102671-7.10132-0.
Singh, P., P. V. M. Lakshmi, S. Prinja, and P. Khanduja. 2018. “Under-reporting of road traffic accidents in traffic police records—A cross sectional study from North India.” Int. J. Commun. Med. Public Health 5 (2): 579. https://doi.org/10.18203/2394-6040.ijcmph20180232.
Singh Bisht, L., and G. Tiwari. 2022. “Safety effects of paved shoulder width on a four-lane divided rural highway in India: A matched case-control study.” Saf. Sci. 147 (Nov): 105606. https://doi.org/10.1016/j.ssci.2021.105606.
Staton, C., et al. 2016. “Road traffic injury prevention initiatives: A systematic review and metasummary of effectiveness in low and middle income countries.” PLoS One 11 (1): e0144971. https://doi.org/10.1371/journal.pone.0144971.
Stockholm Declaration. 2020. “Sweden, 4.” Accessed 10 June 2022. https://www.roadsafetysweden.com/about-the-conference/stockholm-declaration/.
The World Bank. 2020. Guide for road safety opportunities and challenges: Low- and middle-income countries country profile. Washington, DC: The World Bank.
Tiwari, G. 2021. “Principles for development of safer rural highway systems for conditions prevailing in low and middle-income countries.” In Transactions in civil and environmental engineering, edited by G. Tiwari and D. Mohan, 105–127. Singapore: Springer. https://doi.org/10.1007/978-981-16-1115-5_6.
Tiwari, G., R. Goel, and K. Bhalla. 2022. Road safety in India status report 2021. New Delhi, India: Transportation Research and Injury Prevention Center.
Uddin, M., and N. Huynh. 2020. “Injury severity analysis of truck-involved crashes under different weather conditions.” Accid. Anal. Prev. 141 (Jul): 105529. https://doi.org/10.1016/j.aap.2020.105529.
Ukkusuri, S., S. Hasan, and H. M. A. Aziz. 2011. “Random parameter model used to explain effects of built-environment characteristics on pedestrian crash frequency.” Transp. Res. Rec. 2237 (1): 98–106. https://doi.org/10.3141/2237-11.
Vayalamkuzhi, P., and V. Amirthalingam. 2016a. “Development of comprehensive crash models for four-lane divided highways in heterogeneous traffic condition.” Transp. Res. Procedia 17 (Dec): 626–635. https://doi.org/10.1016/j.trpro.2016.11.117.
Vayalamkuzhi, P., and V. Amirthalingam. 2016b. “Influence of geometric design characteristics on safety under heterogeneous traffic flow.” J. Traffic Transp. Eng. 3 (6): 559–570. https://doi.org/10.1016/j.jtte.2016.05.006.
Vayalamkuzhi, P., A. Basu, and V. Amirthalingam. 2016. “Analysis on the level of safety of multi-lane rural highway under heterogenous traffic condition.” In Proc., TRB 95th Annual Meeting Compendium of Papers. Washington, DC; Transportation Research Board.
Venkataraman, N., V. Shankar, G. F. Ulfarsson, and D. Deptuch. 2014. “A heterogeneity-in-means count model for evaluating the effects of interchange type on heterogeneous influences of interstate geometrics on crash frequencies.” Anal. Methods Accid. Res. 2 (Apr): 12–20. https://doi.org/10.1016/j.amar.2014.01.001.
Venkataraman, N., G. F. Ulfarsson, and V. N. Shankar. 2013. “Random parameter models of interstate crash frequencies by severity, number of vehicles involved, collision and location type.” Accid. Anal. Prev. 59 (Oct): 309–318. https://doi.org/10.1016/j.aap.2013.06.021.
Venkataraman, N. S. 2014. “Random parameter analysis of geometric effects on freeway crash occurrence.” Ph.D. dissertation, Faculty of Civil and Environmental Engineering, Univ. of Iceland.
Venkataraman, N. S., G. F. Ulfarsson, V. Shankar, J. Oh, and M. Park. 2011. “Model of relationship between interstate crash occurrence and geometrics: Exploratory insights from random parameter negative binomial approach.” Transp. Res. Rec. 2236 (1): 41. https://doi.org/10.3141/2236-05.
Wang, C., F. Chen, J. Cheng, W. Bo, P. Zhang, M. Hou, and F. Xiao. 2020. “Random-parameter multivariate negative binomial regression for modeling impacts of contributing factors on the crash frequency by crash types.” Discrete Dyn. Nat. Soc. 2020: 6621752. https://doi.org/10.1155/2020/6621752.
Wang, C., F. Chen, Y. Zhang, and J. Cheng. 2022a. “Analysis of injury severity in rear-end crashes on an expressway involving different types of vehicles using random-parameters logit models with heterogeneity in means and variances.” Transp. Lett. 1–12. https://doi.org/10.1080/19427867.2022.2086760.
Wang, C., M. A. Quddus, and S. G. Ison. 2013. “The effect of traffic and road characteristics on road safety: A review and future research direction.” Saf. Sci. 57 (Aug): 264–275. https://doi.org/10.1016/j.ssci.2013.02.012.
Wang, C., P. Zhang, F. Chen, and J. Cheng. 2022b. “Modeling injury severity for nighttime and daytime crashes by using random parameter logit models accounting for heterogeneity in means and variances.” J. Adv. Transp. 2022: 1–12. https://doi.org/10.1155/2022/7871338.
Wang, J. H., M. A. Abdel-Aty, J. Park, C. Lee, and P. F. Kuo. 2015. “Estimating safety performance trends over time for treatments at intersections in Florida.” Accid. Anal. Prev. 80 (Jul): 37–47. https://doi.org/10.1016/j.aap.2015.03.015.
Wasserstein, R. L., and N. A. Lazar. 2016. “The ASA’s statement on p-values: Context, process, and purpose.” Am. Stat. 70 (2): 129–133. https://doi.org/10.1080/00031305.2016.1154108.
Wasserstein, R. L., A. L. Schirm, and N. A. Lazar. 2019. “Moving to a world beyond ‘.’” Supplement, Am. Stat. 73 (S1): 1–19. https://doi.org/10.1080/00031305.2019.1583913.
Wegman, F. 2017. “The future of road safety: A worldwide perspective.” IATSS Res. 40 (2): 66–71. https://doi.org/10.1016/j.iatssr.2016.05.003.
WHO (World Health Organization). 2018. Global status report on road safety 2018. Geneva: WHO.
Wu, Y., M. Abdel-Aty, Q. Cai, J. Lee, and J. Park. 2018. “Developing an algorithm to assess the rear-end collision risk under fog conditions using real-time data.” Transp. Res. Part C Emerging Technol. 87 (Oct): 11–25. https://doi.org/10.1016/j.trc.2017.12.012.
Xu, P., and H. Huang. 2015. “Modeling crash spatial heterogeneity: Random parameter versus geographically weighting.” Accid. Anal. Prev. 75 (Feb): 16–25. https://doi.org/10.1016/j.aap.2014.10.020.
Ye, F., and D. Lord. 2014. “Comparing three commonly used crash severity models on sample size requirements: Multinomial logit, ordered probit and mixed logit models.” Anal. Methods Accid. Res. 1 (Jan): 72–85. https://doi.org/10.1016/j.amar.2013.03.001.
Yu, M., C. Zheng, and C. Ma. 2020. “Analysis of injury severity of rear-end crashes in work zones: A random parameters approach with heterogeneity in means and variances.” Anal. Methods Accid. Res. 27 (Jul): 100126. https://doi.org/10.1016/j.amar.2020.100126.
Yu, R., Y. Xiong, and M. Abdel-Aty. 2015. “A correlated random parameter approach to investigate the effects of weather conditions on crash risk for a mountainous freeway.” Transp. Res. Part C Emerging Technol. 50 (Aug): 68–77. https://doi.org/10.1016/j.trc.2014.09.016.
Zhang, K. I., and M. Hassan. 2019. “Identifying the factors contributing to injury severity in work zone rear-end crashes.” J. Adv. Transp. 2019: 1–9. https://doi.org/10.1155/2019/4126102.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 29, 2021
Accepted: Jul 22, 2022
Published online: Oct 17, 2022
Published in print: Jan 1, 2023
Discussion open until: Mar 17, 2023
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Laxman Singh Bisht, Geetam Tiwari, A matched case–control approach to identify the risk factors of fatal pedestrian crashes on a six-lane rural highway in India, International Journal of Injury Control and Safety Promotion, 10.1080/17457300.2023.2242336, 30, 4, (612-628), (2023).