A matched case–control approach to identify the risk factors of fatal pedestrian crashes on a six-lane rural highway in India

References

• AASHTO (2010). Highway safety manual (Vol. 1). The American Association of State Highway Transportation Officials (AASHTO).
   Google Scholar
• Abdel-Aty, M., Uddin, N., Pande, A., Abdalla, M. F., & Hsia, L. (2004). Predicting freeway crashes from loop detector data by matched case–control logistic regression. Transportation Research Record: Journal of the Transportation Research Board, 1897(1), 88–95. https://doi.org/10.3141/1897-12
   Google Scholar
• Baireddy, R., Zhou, H., & Jalayer, M. (2018). Multiple correspondence analysis of pedestrian crashes in rural Illinois. Transportation Research Record: Journal of the Transportation Research Board, 2672(38), 116–127. https://doi.org/10.1177/0361198118777088
   Web of Science ®Google Scholar
• Banerjee, A., Raoniar, R., & Maurya, A. K. (2020). Pedestrian overpass utilization smodeling based on mobility friction, safety and security, and connectivity using machine learning techniques. Soft Computing, 24(22), 17467–17493. https://doi.org/10.1007/s00500-020-05277-w
   Web of Science ®Google Scholar
• Basu, S., & Saha, P. (2022). Evaluation of risk factors for road accidents under mixed traffic: Case study on Indian highways. IATSS Research, 46(4), 559–573. https://doi.org/10.1016/j.iatssr.2022.09.004
   Web of Science ®Google Scholar
• Besharati, M. M., & Kashan, A. T. (2018). Which set of factors contribute to increase the likelihood of pedestrian fatality in road crashes? International Journal of Injury Control and Safety Promotion, 25(3), 247–256. https://doi.org/10.1080/17457300.2017.1363781
   PubMed Web of Science ®Google Scholar
• Bisht, L. S., & Tiwari, G. (2022). Safety effects of paved shoulder width on a four-lane divided rural highway in India: A matched case–control study. Safety Science, 147(November 2021), 105606. https://doi.org/10.1016/j.ssci.2021.105606
   Google Scholar
• Bisht, L. S., & Tiwari, G. (2023a). Assessing the effect of paved shoulder width on road traffic crash risk on a six-lane rural highway in India. Journal of Transportation Engineering, Part A: Systems, 149(7), 1–16. https://doi.org/10.1061/JTEPBS.TEENG-7296
   Web of Science ®Google Scholar
• Bisht, L. S., & Tiwari, G. (2023b). Assessment of fatal rear-end crash risk factors of an expressway in India: A random parameter NB modeling approach. Journal of Transportation Engineering, Part A: Systems, 149(1), 1–19. https://doi.org/10.1061/JTEPBS.0000767
   Web of Science ®Google Scholar
• Bisht, L. S., Tiwari, G., Rao, K. R., & Jha, K. N. (2022). Exploratory assessment of road traffic crashes on the intercity expressway in India. Advances in Transportation Studies, 3, 45–58.
   Google Scholar
• Breslow, N. E., Day, N. E., Halvorsen, K. T., Prentice, R. L., & Sabai, C. (1978). Estimation of multiple relative risk functions in matched case–control studies. American Journal of Epidemiology, 108(4), 299–307. https://doi.org/10.1093/oxfordjournals.aje.a112623
   PubMed Web of Science ®Google Scholar
• Cameron, A. C., & Windmeijer, F. A. G. (1996). R-squared measures for count data regression models with applications to health-care utilization. Journal of Business & Economic Statistics, 14(2), 209–220. https://doi.org/10.1080/07350015.1996.10524648
   Web of Science ®Google Scholar
• Carlin, J. B., Taylor, P., & Nolan, T. (1995). A case–control study of child bicycle injuries: Relationship of risk to exposure. Accident; Analysis and Prevention, 27(6), 839–844. https://doi.org/10.1016/0001-4575(95)00032-1
   PubMed Web of Science ®Google Scholar
• Carter, D. L., & Council, F. M. (2006). Factors contributing to pedestrian and bicycle crashes on rural highways (Issue June).
   Google Scholar
• Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier Inc.
   Google Scholar
• Dinh, D. D., Vũ, N. H., McIlroy, R. C., Plant, K. A., & Stanton, N. A. (2020). Effect of attitudes towards traffic safety and risk perceptions on pedestrian behaviours in Vietnam. IATSS Research, 44(3), 238–247. https://doi.org/10.1016/j.iatssr.2020.01.002
   Web of Science ®Google Scholar
• Edwards, M., & Leonard, D. (2022). Effects of large vehicles on pedestrian and pedalcyclist injury severity. Journal of Safety Research, 82, 275–282. https://doi.org/10.1016/j.jsr.2022.06.005
   PubMed Web of Science ®Google Scholar
• Elvik, R. (2002). The importance of confounding in observational before-and-after studies of road safety measures. Accident; Analysis and Prevention, 34(5), 631–635. https://doi.org/10.1016/s0001-4575(01)00062-8
   PubMed Web of Science ®Google Scholar
• Elvik, R. (2004). To what extent can theory account for the findings of road safety evaluation studies?. Accident Analysis & Prevention, 36(5), 841–849. https://doi.org/10.1016/j.aap.2003.08.003
   Google Scholar
• Fredriksson, R., & Rosén, E. (2012). Integrated pedestrian countermeasures – Potential of head injury reduction combining passive and active countermeasures. Safety Science, 50(3), 400–407. https://doi.org/10.1016/j.ssci.2011.09.019
   Web of Science ®Google Scholar
• Gitelman, V., Doveh, E., Carmel, R., & Hakkert, S. (2019). The influence of shoulder characteristics on the safety level of two-lane roads: A case-study. Accident; Analysis and Prevention, 122(October 2018), 108–118. https://doi.org/10.1016/j.aap.2018.10.003
   PubMedGoogle Scholar
• Goel, R., Jain, P., & Tiwari, G. (2018). Correlates of fatality risk of vulnerable road users in Delhi. Accident; Analysis and Prevention, 111, 86–93. https://doi.org/10.1016/j.aap.2017.11.023
   PubMed Web of Science ®Google Scholar
• Gooch, J., Hamilton, I., Polin, B., Tanzen, R., & Cohen, T. (2022). Systemic safety analysis of midblock pedestrian crashes in Massachusetts. Transportation Research Record: Journal of the Transportation Research Board, 2676(11), 722–730. https://doi.org/10.1177/03611981221094566
   Web of Science ®Google Scholar
• Gross, F. (2013). Case–control analysis in highway safety: Accounting for sites with multiple crashes. Accident; Analysis and Prevention, 61, 87–96. https://doi.org/10.1016/j.aap.2012.05.013
   PubMed Web of Science ®Google Scholar
• Gross, F., & Donnell, E. T. (2011). Case–control and cross-sectional methods for estimating crash modification factors: Comparisons from roadway lighting and lane and shoulder width safety effect studies. Journal of Safety Research, 42(2), 117–129. https://doi.org/10.1016/j.jsr.2011.03.003
   PubMed Web of Science ®Google Scholar
• Gross, F., & Jovanis, P. P. (2007a). Estimation of safety effectiveness of changes in shoulder width with case control and cohort methods. Transportation Research Record: Journal of the Transportation Research Board, 2019(1), 237–245. https://doi.org/10.3141/2019-28
   Google Scholar
• Gross, F., & Jovanis, P. P. (2007b). Estimation of the safety effectiveness of lane and shoulder width: Case–control approach. Journal of Transportation Engineering, 133(6), 362–369. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:6(362)
   Web of Science ®Google Scholar
• Gross, F., Persaud, B., & Lyon, C. (2010). A guide to developing quality crash modification factors.
   Google Scholar
• Hall, J. W. (1980). Pedestrian accidents on rural highways. Transport Research Record, 904, 46–50.
   Google Scholar
• Harwood, D. W., Council, F. M., Hauer, E., Hughes, W. E., & Vogt, A. (2000). Prediction of the expected safety performance of rural two-lane highways. Federal Highway Administration, U.S. Department of Transportation.
   Google Scholar
• Hauer, E. (1992). Empirical Bayes approach to the estimation of “unsafety”: The multivariate regression method. Accident; Analysis and Prevention, 24(5), 457–477. https://doi.org/10.1016/0001-4575(92)90056-o
   PubMed Web of Science ®Google Scholar
• Hauer, E. (2010). Cause, effect and regression in road safety: A case study. Accident; Analysis and Prevention, 42(4), 1128–1135. https://doi.org/10.1016/j.aap.2009.12.027
   PubMed Web of Science ®Google Scholar
• Hauer, E., Harwood, D. W., Council, F. M., & Griffith, M. S. (2002). Estimating safety by the EB method. Transportation Research Record: Journal of the Transportation Research Board, 1784(1), 126–131. https://doi.org/10.3141/1784-16
   Google Scholar
• Hezaveh, A. M., & Cherry, C. R. (2018). Walking under the influence of the alcohol: A case study of pedestrian crashes in Tennessee. Accident; Analysis and Prevention, 121(August), 64–70. https://doi.org/10.1016/j.aap.2018.09.002
   PubMedGoogle Scholar
• Hijar, M., Carrillo, C., Flores, M., Anaya, R., & Lopez, V. (2000). Risk factors in highway traffic accidents: A case control study. Accident; Analysis and Prevention, 32(5), 703–709. https://doi.org/10.1016/S0001-4575(99)00116-5
   PubMed Web of Science ®Google Scholar
• Hilbe, J. M. (2009). Logistic regression models. Chapman and Hall; CRC.
   Google Scholar
• Hsiao, M., Malhotra, A., Thakur, J. S., Sheth, J. K., Nathens, A. B., Dhingra, N., & Jha, P. (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
   PubMed Web of Science ®Google Scholar
• Hu, W., & Cicchino, J. B. (2018). An examination of the increases in pedestrian motor-vehicle crash fatalities during 2009–2016. Journal of Safety Research, 67, 37–44. https://doi.org/10.1016/j.jsr.2018.09.009
   PubMed Web of Science ®Google Scholar
• IRC (2019). IRC:SP:87-2019 manual of specifications and standards for six laning of highways (second revision). The Indian Roads Congress (IRC).
   Google Scholar
• Islam, S., & Jones, S. L. (2014). Pedestrian at-fault crashes on rural and urban roadways in Alabama. Accident; Analysis and Prevention, 72, 267–276. https://doi.org/10.1016/j.aap.2014.07.003
   PubMed Web of Science ®Google Scholar
• Job, R. F. S. (2020). Policies and interventions to provide safety for pedestrians and overcome the systematic biases underlying the failures. Frontiers in Sustainable Cities, 2(June), 1–8. https://doi.org/10.3389/frsc.2020.00030
   Google Scholar
• Kadali, B. R., & Vedagiri, P. (2016). Proactive pedestrian safety evaluation at unprotected mid-block crosswalk locations under mixed traffic conditions. Safety Science, 89, 94–105. https://doi.org/10.1016/j.ssci.2016.05.014
   Web of Science ®Google Scholar
• Kashani, A. T., & Besharati, M. M. (2017). Fatality rate of pedestrians and fatal crash involvement rate of drivers in pedestrian crashes: A case study of Iran. International Journal of Injury Control and Safety Promotion, 24(2), 222–231. https://doi.org/10.1080/17457300.2016.1166139
   PubMed Web of Science ®Google Scholar
• Kvasnes, S., Pokorny, P., Jensen, J. K., & Pitera, K. (2021). Safety effects of horizontal curve design and lane and shoulder width on single motorcycle accidents in Norway. Journal of Advanced Transportation, 2021, 1–11. https://doi.org/10.1155/2021/6684334
   Web of Science ®Google Scholar
• Lee, C., & Abdel-Aty, M. (2005). Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accident; Analysis and Prevention, 37(4), 775–786. https://doi.org/10.1016/j.aap.2005.03.019
   PubMed Web of Science ®Google Scholar
• Lee, J., Abdel-Aty, M., Choi, K., & Huang, H. (2015). Multi-level hot zone identification for pedestrian safety. Accident; Analysis and Prevention, 76, 64–73. https://doi.org/10.1016/j.aap.2015.01.006
   PubMed Web of Science ®Google Scholar
• Li, Q., Wang, Z., Li, M., Yang, R., Lin, P. S., & Li, X. (2021). Development of crash modification factors for roadway illuminance: A matched case–control study. Accident; Analysis and Prevention, 159(February), 106279. https://doi.org/10.1016/j.aap.2021.106279
   PubMedGoogle Scholar
• Li, Q., Yao, H., & Li, X. (2023). A matched case–control method to model car-following safety. Transportmetrica A: Transport Science, 19(3), 1–19. https://doi.org/10.1080/23249935.2022.2055198
   Web of Science ®Google Scholar
• Li, Y., & Fan, W. (D.). (2019). Modelling severity of pedestrian-injury in pedestrian-vehicle crashes with latent class clustering and partial proportional odds model: A case study of North Carolina. Accident; Analysis and Prevention, 131(July), 284–296. https://doi.org/10.1016/j.aap.2019.07.008
   PubMedGoogle Scholar
• Li, Y., & Fernie, G. (2010). Pedestrian behavior and safety on a two-stage crossing with a center refuge island and the effect of winter weather on pedestrian compliance rate. Accident; Analysis and Prevention, 42(4), 1156–1163. https://doi.org/10.1016/j.aap.2010.01.004
   PubMed Web of Science ®Google Scholar
• Lord, D., Qin, X., & Geedipally, S. R. (2021). Highway safety analytics and modeling. Elsevier. https://doi.org/10.1016/c2018-0-00207-8
   Google Scholar
• Lumley, T., Elizabeth, A., Cynthia, C., & Therneau, M. T. M. (2023). Package ‘survival’.
   Google Scholar
• MacLeod, K. E., Griswold, J. B., Arnold, L. S., & Ragland, D. R. (2012). Factors associated with hit-and-run pedestrian fatalities and driver identification. Accident; Analysis and Prevention, 45, 366–372. https://doi.org/10.1016/j.aap.2011.08.001
   PubMed Web of Science ®Google Scholar
• Mahdinia, I., Khattak, A. J., & Mohsena Haque, A. (2022). How effective are pedestrian crash prevention systems in improving pedestrian safety? Harnessing large-scale experimental data. Accident; Analysis and Prevention, 171(November 2021), 106669. https://doi.org/10.1016/j.aap.2022.106669
   PubMedGoogle Scholar
• 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. https://doi.org/10.1016/j.amar.2016.04.001
   Web of Science ®Google Scholar
• Martin, A. (2006). Factors influencing pedestrian safety: A literature review.
   Google Scholar
• Medury, A., Grembek, O., Loukaitou-Sideris, A., & Shafizadeh, K. (2019). Investigating the underreporting of pedestrian and bicycle crashes in and around university campuses – A crowdsourcing approach. Accident; Analysis and Prevention, 130(August 2017), 99–107. https://doi.org/10.1016/j.aap.2017.08.014
   PubMedGoogle Scholar
• Mirhashemi, A., Amirifar, S., Tavakoli, A., & Zou, X. (2022). Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends. Accident; Analysis and Prevention, 174(January), 106720. https://doi.org/10.1016/j.aap.2022.106720
   PubMedGoogle Scholar
• Mitra, S., & Washington, S. (2012). On the significance of omitted variables in intersection crash modeling. Accident; Analysis and Prevention, 49, 439–448. https://doi.org/10.1016/j.aap.2012.03.014
   PubMed Web of Science ®Google Scholar
• Mitra, S., Haque, M., & King, M. J. (2017). Effects of access, geometric design, and heterogeneous traffic on safety performance of divided multilane highways in India. Journal of Transportation Safety & Security, 9(sup1), 216–235. https://doi.org/10.1080/19439962.2016.1237600
   Web of Science ®Google Scholar
• Mohan, D. (2002). Road safety in less-motorized environments: Future concerns. International Journal of Epidemiology, 31(3), 527–532. https://doi.org/10.1093/ije/31.3.527
   PubMed Web of Science ®Google Scholar
• Mohan, D., Jha, A., & Chauhan, S. S. (2021). Future of road safety and SDG 3.6 goals in six Indian cities. IATSS Research, 45(1), 12–18. https://doi.org/10.1016/j.iatssr.2021.01.004
   Web of Science ®Google Scholar
• MoRTH (2018). The Gazette of India: Extraordinary-Part II-Section 3-Sub-section (ii).
   Google Scholar
• MoRTH (2022a). Annual report 2021–2022.
   Google Scholar
• MoRTH (2022b). Road accidents in India 2021.
   Google Scholar
• Mukherjee, D., & Mitra, S. (2020). A comprehensive study on factors influencing pedestrian signal violation behaviour: Experience from Kolkata City, India. Safety Science, 124(April 2019), 104610. https://doi.org/10.1016/j.ssci.2020.104610
   Google Scholar
• Mukherjee, D., & Mitra, S. (2022). Development of a systematic methodology to enhance the safety of vulnerable road users in developing countries. Transportation in Developing Economies, 8(2), 1–17. https://doi.org/10.1007/s40890-022-00165-4
   Web of Science ®Google Scholar
• Naqvi, H. M., & Tiwari, G. (2022). Factors explaining pedestrian-involved fatality crashes on National Highways in India. International Journal of Injury Control and Safety Promotion, 29(3), 321–330. https://doi.org/10.1080/17457300.2022.2029910
   PubMed Web of Science ®Google Scholar
• Nasar, J. L., & Troyer, D. (2013). Pedestrian injuries due to mobile phone use in public places. Accident; Analysis and Prevention, 57, 91–95. https://doi.org/10.1016/j.aap.2013.03.021
   PubMed Web of Science ®Google Scholar
• NHTSA (2018). Critical reasons for crashes investigated in the national motor vehicle crash causation survey.
   Google Scholar
• Öström, M., & Eriksson, A. (2001). Pedestrian fatalities and alcohol. Accident; Analysis and Prevention, 33(2), 173–180. https://doi.org/10.1016/S0001-4575(00)00028-2
   PubMed Web of Science ®Google Scholar
• Pokorny, P., Jensen, J. K., Gross, F., & Pitera, K. (2020). Safety effects of traffic lane and shoulder widths on two-lane undivided rural roads: A matched case–control study from Norway. Accident; Analysis and Prevention, 144(February), 105614. https://doi.org/10.1016/j.aap.2020.105614
   PubMedGoogle Scholar
• Pour-Rouholamin, M., & Zhou, H. (2016). Investigating the risk factors associated with pedestrian injury severity in Illinois. Journal of Safety Research, 57, 9–17. https://doi.org/10.1016/j.jsr.2016.03.004
   PubMed Web of Science ®Google Scholar
• Raoniar, R., & Maurya, A. K. (2022). Pedestrian red-light violation at signalized intersection crosswalks: Influence of social and non-social factors. Safety Science, 147(September 2020), 105583. https://doi.org/10.1016/j.ssci.2021.105583
   Google Scholar
• Rumar, K. (1985). The role of perceptual and cognitive filters in observed behavior. In Human behavior and traffic safety (pp. 151–170). Springer. https://doi.org/10.1007/978-1-4613-2173-6_8
   Google Scholar
• Sarkar, S., Tay, R., & Hunt, J. D. (2011). Logistic regression model of risk of fatality in vehicle-pedestrian crashes on national highways in Bangladesh. Transportation Research Record: Journal of the Transportation Research Board, 2264(1), 128–137. https://doi.org/10.3141/2264-15
   Google Scholar
• Schlesselman, J. J. (1982). Case–control studies: Design, conduct, analysis (Vol. 2). Oxford University Press.
   Google Scholar
• Schneider, R. J., Diogenes, M. C., Arnold, L. S., Attaset, V., Griswold, J., & Ragland, D. R. (2010). Association between roadway intersection characteristics and pedestrian crash risk in Alameda County, California. Transportation Research Record: Journal of the Transportation Research Board, 2198(1), 41–51. https://doi.org/10.3141/2198-06
   Google Scholar
• Shoabjareh, A. H., Mamdoohi, A. R., & Nordfjærn, T. (2021). Analysis of pedestrians’ behaviour: A segmentation approach based on latent variables. Accident; Analysis and Prevention, 157(April), 106160. https://doi.org/10.1016/j.aap.2021.106160
   PubMedGoogle Scholar
• Sivasankaran, S. K., & Balasubramanian, V. (2022). Investigation of factors contributing to pedestrian hit-and-run crashes in India. Journal of Transportation Safety & Security, 14(3), 382–403. https://doi.org/10.1080/19439962.2020.1781313
   Web of Science ®Google Scholar
• Sun, M., Sun, X., & Shan, D. (2019). Pedestrian crash analysis with latent class clustering method. Accident; Analysis and Prevention, 124(December 2018), 50–57. https://doi.org/10.1016/j.aap.2018.12.016
   PubMedGoogle Scholar
• Tay, R., Choi, J., Kattan, L., & Khan, A. (2011). A multinomial logit model of pedestrian-vehicle crash severity. International Journal of Sustainable Transportation, 5(4), 233–249. https://doi.org/10.1080/15568318.2010.497547
   Web of Science ®Google Scholar
• Tester, J. M., Rutherford, G. W., Wald, Z., & Rutherford, M. W. (2004). A matched case–control study evaluating the effectiveness of speed humps in reducing child pedestrian injuries. American Journal of Public Health, 94(4), 646–650. https://doi.org/10.2105/AJPH.94.4.646
   PubMed Web of Science ®Google Scholar
• Tiwari, G. (2020). Progress in pedestrian safety research. International Journal of Injury Control and Safety Promotion, 27(1), 35–43. https://doi.org/10.1080/17457300.2020.1720255
   PubMed Web of Science ®Google Scholar
• Tiwari, G. (2021). Principles for development of safer rural highway systems for conditions prevailing in low and middle-income countries. In Transport and safety (pp. 105–127). Springer.
   Google Scholar
• Tiwari, G., & Nishant. (2018). Travel to work in India: Current patterns and future concerns.
   Google Scholar
• Tiwari, G., Goel, R., & Bhalla, K. (2022). Road safety in India: Status report 2021. Retrieved from https://tripc.iitd.ac.in/assets/publication/TRIPC_status_report_Aug222.pdf
   Google Scholar
• Tulu, G. S., Washington, S., Haque, M. M., & King, M. J. (2015). Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia. Accident; Analysis and Prevention, 78, 118–126. https://doi.org/10.1016/j.aap.2015.02.011
   PubMed Web of Science ®Google Scholar
• Vignali, V., Cuppi, F., Acerra, E., Bichicchi, A., Lantieri, C., Simone, A., & Costa, M. (2019). Effects of median refuge island and flashing vertical sign on conspicuity and safety of unsignalized crosswalks. Transportation Research Part F: Traffic Psychology and Behaviour, 60, 427–439. https://doi.org/10.1016/j.trf.2018.10.033
   Web of Science ®Google Scholar
• Wanvik, P. O. (2009). Effects of road lighting: An analysis based on Dutch accident statistics 1987–2006. Accident; Analysis and Prevention, 41(1), 123–128. https://doi.org/10.1016/j.aap.2008.10.003
   PubMed Web of Science ®Google Scholar
• Washington, S. P., Karlaftis, M. G., & Mannering, F. (2010). Statistical and econometric methods for transportation data analysis. Chapman and Hall; CRC.
   Google Scholar
• WHO (2013). Pedestrian safety A road safety manual for decision-makers and practitioners.
   Google Scholar
• WHO (2018). Global status report on road safety 2018.
   Google Scholar
• Wissmann, M., Toutenburg, H., & Shalabh. (2007). Role of categorical variables in multicollinearity in the linear regression model. Technical Report Number, Department of Statistics University of Munich, 008 (pp. 1–34). Retrieved from http://www.stat.uni-muenchen.de
   Google Scholar
• Woodward, M. (2014). Epidemiology study design and data analysis. CRC Press.
   Google Scholar
• Xie, X., Nikitas, A., & Liu, H. (2018). A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China. Traffic Injury Prevention, 19(3), 298–304. https://doi.org/10.1080/15389588.2017.1387654
   PubMed Web of Science ®Google Scholar
• Zajac, S. S., & Ivan, J. N. (2003). Factors influencing injury severity of motor vehicle-crossing pedestrian crashes in rural Connecticut. Accident; Analysis and Prevention, 35(3), 369–379. https://doi.org/10.1016/S0001-4575(02)00013-1
   PubMed Web of Science ®Google Scholar
• Zhang, C., Zhou, B., Chen, G., & Chen, F. (2017). Quantitative analysis of pedestrian safety at uncontrolled multilane mid-block crosswalks in China. Accident; Analysis and Prevention, 108(August), 19–26. https://doi.org/10.1016/j.aap.2017.08.018
   PubMedGoogle Scholar
• Zhang, G., Yau, K. K. W., & Zhang, X. (2014). Analyzing fault and severity in pedestrian-motor vehicle accidents in China. Accident; Analysis and Prevention, 73, 141–150. https://doi.org/10.1016/j.aap.2014.08.018
   PubMed Web of Science ®Google Scholar
• Zheng, Z., Ahn, S., & Monsere, C. M. (2010). Impact of traffic oscillations on freeway crash occurrences. Accident; Analysis and Prevention, 42(2), 626–636. https://doi.org/10.1016/j.aap.2009.10.009
   PubMed Web of Science ®Google Scholar