Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410075 PR China.
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
Accid Anal Prev. 2019 Jan;122:318-324. doi: 10.1016/j.aap.2018.10.017. Epub 2018 Nov 6.
Pedestrians are vulnerable to severe injury and mortality in road crashes. Numerous studies have attempted to identify factors contributing to crashes and pedestrian injury risks. As an active transport mode, the act of walking is sensitive to changes in weather conditions. However, comprehensive real-time weather data are often unavailable for road safety analysis. In this study, we used a geographical information system approach to integrate high-resolution weather data, as well as their corresponding temporal and spatial distributions, with crash data. Then, we established a mixed logit model to determine the association between pedestrian crash severity and possible risk factors. The results indicate that high temperature and the presence of rain were associated with a higher likelihood of Killed and Severe Injury (KSI) crashes. Also, we found the interaction effects of weather condition (hot weather and presence of rain) on the association between pedestrian crash severity and pedestrian and driver behaviors to be significant. For instance, the effects of jaywalking and risky driving behavior on crash severity were more prevalent under rainy conditions. In addition, the effects of driver inattention and reckless crossing were more significant in hot weather conditions. This has critical policy implications for the development and implementation of proactive traffic management systems. For instance, real-time weather and traffic data should be incorporated into dynamic message signs and in-vehicle warning systems. Doing so will enhance the levels of safety awareness of drivers and pedestrians, especially in adverse weather conditions. As a result, pedestrian safety can be improved over the long term.
行人在道路事故中容易受到重伤和死亡的伤害。许多研究试图确定导致事故和行人受伤风险的因素。作为一种积极的交通方式，行走行为对天气条件的变化很敏感。然而，全面的实时天气数据通常无法用于道路安全分析。在这项研究中，我们使用地理信息系统方法将高分辨率天气数据及其相应的时间和空间分布与碰撞数据集成。然后，我们建立了一个混合逻辑模型来确定行人碰撞严重程度与可能的风险因素之间的关联。结果表明，高温和下雨与 Killed 和严重伤害（KSI）碰撞的可能性更高有关。此外，我们发现天气条件（炎热天气和下雨）对行人碰撞严重程度与行人行为和司机行为之间关联的交互作用是显著的。例如，在下雨条件下，乱穿马路和冒险驾驶行为对碰撞严重程度的影响更为普遍。此外，在炎热天气条件下，司机注意力不集中和鲁莽穿越的影响更为显著。这对开发和实施主动交通管理系统具有重要的政策意义。例如，应将实时天气和交通数据纳入动态信息标志和车载警告系统。这样做将提高司机和行人的安全意识水平，特别是在恶劣天气条件下。因此，从长远来看，可以提高行人的安全性。
