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Roadside barriers have proven effective in preventing run-off-road accidents that occurred in mountainous areas. Nonetheless, the influence of variables impacting the severity of injuries resulting from collisions involving distinct types of roadside barriers may diverge. This study delves into the factors that influence the severity of driver's injuries in crashes encompassing three specific varieties of roadside barriers in mountainous regions, namely, W-beam barriers, flexible barriers, and roadside trees. The evolution of these factors over time is examined through the application of a random parameters logit modeling approach with heterogeneity in means and variances (RPLHMVs). By employing injury-severity data from 2016 to 2019 for the mountainous regions of a city in Southwest China, various potential influencing factors encompassing driver-, vehicle-, road-, and environment-specific characteristics are subjected to statistical analysis. The extent of the impact of identified statistically significant factors on driver's injury severity is assessed through the computation of pseudoelasticities. The findings reveal distinctions in the outcomes of driver's injury severity contingent upon the type of roadside barrier encountered during vehicle impacts. To illustrate, collisions involving W-beam barriers are more prone to result in severe injuries. Moreover, the influence of variables determining driver's injury severity displays noteworthy temporal shifts. Notably, the pseudoelasticities of numerous explanatory variables remain temporally consistent for incidents involving flexible or roadside barriers. In contrast, crashes involving W-beam barriers highlight that solely the speeding indicator demonstrates temporally stable pseudoelasticities. The insights garnered from this investigation offer the potential to contribute to the formulation of fresh guidelines for the design and selection of roadside barriers aimed at mitigating the severity of injuries incurred in crashes within mountainous regions., Author(s): Chunhui Zhang [1]; Yanying Wang [2]; Keqi Wu [3]; Le Tian [2]; Dongdong Song (corresponding author) [4] 1. Introduction Over 15% of traffic incidents transpired within mountainous terrains during [...]

This study proposes random-parameters multinomial logit models, with heterogeneity in means and variances, to explore the differences in the factors influencing injury severities of drivers involved in different types of two-vehicle crashes. The models are verified using crash data from the United Kingdom (UK) over three years (2016-2018). Three types of crashes are separately identified (car-car, car-truck, and truck-truck crashes). In this study, a wide variety of potential variables, including the driver, vehicle, road, and environmental characteristics, are considered, with two possible injury-severity outcomes: severe and slight injury. The results show that unobserved heterogeneity existed for young drivers in both car-car and truck-truck crash models and the 30mph speed limit in the three separate models. Remarkably variations are observed in crashes involving different types of vehicles. The driver's age and gender, speeding, sideswipes, presence of junctions, weekdays, unlit, and weather conditions significantly impact driver-injury severities in various types of vehicle crashes. These findings are expected to help policymakers seek to improve highway safety and implement proper safety countermeasures., Author(s): Qiang Wu [1]; Dongdong Song (corresponding author) [2]; Chenzhu Wang (corresponding author) [3]; Fei Chen [3]; Jianchuan Cheng [3]; Said M. Easa [4]; Yitao Yang [5]; Wenchen Yang [6,7] [...]