References
- Al-Bdairi NSS, Behnood A, Hernandez S. 2020. Temporal stability of driver injury severities in animal-vehicle collisions: a random parameters with heterogeneity in means (and variances) approach. Anal Methods Accid Res. 26:100120. doi:https://doi.org/10.1016/j.amar.2020.100120
- AlKheder S, AlRukaibi F, Aiash A. 2020. Risk analysis of traffic accidents' severities: an application of three data mining models. ISA Trans. 106:213–220. doi:https://doi.org/10.1016/j.isatra.2020.06.018
- Casado-Sanz N, Guirao B, Gálvez-Pérez D. 2019. Population ageing and rural road accidents: analysis of accident severity in traffic crashes with older pedestrians on Spanish crosstown roads. Res Transp Bus Manag. 30(February):100377. doi:https://doi.org/10.1016/j.rtbm.2019.100377
- Fountas G, Anastasopoulos PC, Mannering FL. 2018. Analysis of vehicle accident-injury severities: a comparison of segment- versus accident-based latent class ordered probit models with class-probability functions. Anal Methods Accid Res. 18:15–32. doi:https://doi.org/10.1016/j.amar.2018.03.003
- Fountas G, Fonzone A, Gharavi N, Rye T. 2020. The joint effect of weather and lighting conditions on injury severities of single-vehicle accidents. Anal Methods Accid Res. 27:100124. doi:https://doi.org/10.1016/j.amar.2020.100124
- Gennarelli TA, Wodzin E. 2006. AIS 2005: a contemporary injury scale. Injury. 37(12):1083–1091. https://www.sciencedirect.com/science/article/pii/S0020138306004190. doi:https://doi.org/10.1016/j.injury.2006.07.009
- Ghosh A, Dey P. 2021. Flood Severity assessment of the coastal tract situated between Muriganga and Saptamukhi estuaries of Sundarban delta of India using Frequency Ratio (FR), Fuzzy Logic (FL), Logistic Regression (LR) and Random Forest (RF) models. Reg Stud Mar Sci. 42:101624. doi:https://doi.org/10.1016/j.rsma.2021.101624
- Hu L, Bao X, Lin M, Yu C, Wang F. 2021. Research on risky driving behavior evaluation model based on CIDAS real data. Proc Inst Mech Eng Part D J Automob Eng. 235(8):2176–2187. doi:https://doi.org/10.1177/0954407020985972
- Hu L, Hu X, Wang J, Kuang A, Hao W, Lin M. 2020. Casualty risk of e-bike rider struck by passenger vehicle using China in-depth accident data. Traffic Inj Prev. 21(4):283–287. doi:https://doi.org/10.1080/15389588.2020.1747614
- Hu L, Ou J, Huang J, Wang F, Wang Y, Ren B, Peng H, Zhou L. 2021. Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China. J Transp Saf Secur. doi:https://doi.org/10.1080/19439962.2021.1960662
- Hu L, Wu X, Huang J, Peng Y, Liu W. 2020. Investigation of clusters and injuries in pedestrian crashes using GIS in Changsha, China. Saf Sci. 127(November 2019):104710. doi:https://doi.org/10.1016/j.ssci.2020.104710
- Huang H, Chang F, Zhou H, Lee J. 2019. Modeling unobserved heterogeneity for zonal crash frequencies: a Bayesian multivariate random-parameters model with mixture components for spatially correlated data. Anal Methods Accid Res. 24:100105. doi:https://doi.org/10.1016/j.amar.2019.100105
- Huang J, Chen Y, Peng X, Hu L, Cao D. 2020. Study on the driving style adaptive vehicle longitudinal control strategy. IEEE/CAA J Autom Sinica. 7(4):1107–1115. doi:https://doi.org/10.1109/JAS.2020.1003261
- Hyodo S, Hasegawa K. 2021. Factors affecting analysis of the severity of accidents in cold and snowy areas using the ordered probit model. Asian Transp Stud. 7(February):100035. doi:https://doi.org/10.1016/j.eastsj.2021.100035
- Li J, Fang S, Guo J, Fu T, Qiu M. 2021. A motorcyclist-injury severity analysis: a comparison of single-, two-, and multi-vehicle crashes using latent class ordered probit model. Accid Anal Prev. 151(October 2020):105953. doi:https://doi.org/10.1016/j.aap.2020.105953
- National Bureau of Statistics P. National data. 2020. https://data.stats.gov.cn/easyquery.htm?cn=C01. Accessed March 26, 2022.
- Oberski D. 2016. Mixture models: latent profile and latent class analysis. In: Robertson J, Kaptein M, editors. BT - modern statistical methods for HCI. Cham: Springer International Publishing. p. 275–287. https://doi.org/10.1007/978-3-319-26633-6_12.
- Sun X, Cai W, Li M. 2021. A hierarchical modeling approach for degradation data with mixed-type covariates and latent heterogeneity. Reliab Eng Syst Saf. 216(July):107928. doi:https://doi.org/10.1016/j.ress.2021.107928
- Theofilatos A, Yannis G, Antoniou C, Chaziris A, Sermpis D. 2018. Time series and support vector machines to predict powered-two-wheeler accident risk and accident type propensity: a combined approach. J Transp Saf Secur. 10(5):471–490.
- Tirtha SD, Yasmin S, Eluru N. 2020. Modeling of incident type and incident duration using data from multiple years. Anal Methods Accid Res. 28:100132. doi:https://doi.org/10.1016/j.amar.2020.100132
- Wang F, Wu J, Hu L, Yu C, Wang B, Huang X, Miller K, Wittek A. 2022. Evaluation of the head protection effectiveness of cyclist helmets using full-scale computational biomechanics modelling of cycling accidents. J Safety Res. 80:109–134. doi:https://doi.org/10.1016/j.jsr.2021.11.005
- Wang W, Jiang X, Xia S, Cao Q. 2010. Incident tree model and incident tree analysis method for quantified risk assessment: an in-depth accident study in traffic operation. Saf Sci. 48(10):1248–1262. doi:https://doi.org/10.1016/j.ssci.2010.04.002
- Weng J, Gan X, Chen J. 2021. A separate analysis of crash frequency for the highways involving traffic hazards and involving no traffic hazards. J Transp Saf Secur. 13(8):822–841. doi:https://doi.org/10.1080/19439962.2019.1690086
- Wu Q, Zhang G, Ci Y, Wu L, Tarefder RA, Alcántara A. 2016. Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes. Traffic Inj Prev. 17(4):413–422.
- Xie X, Nikitas A, Liu H. 2018. A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China. Traffic Inj Prev. 19(3):298–304. doi:https://doi.org/10.1080/15389588.2017.1387654