Adverse weather could potentially increase the probability of driving errors and hazardous driving actions and it is necessary to explicitly understand the endogenous and exogenous mechanism of how adverse weather-related determinants influence crash-injury severities and explore their spatiotemporal stability. To investigate the heterogeneity and spatiotemporal stability of adverse-weather-related crash severity determinants, this paper estimated two groups of random parameters multinomial logit models with heterogeneity in the means and variances. Crash data from Ohio and California were utilized between January 1, 2013 and December 31, 2016. Three crash injury severity categories were investigated including no injury, minor injury, and severe injury, in terms of multiple factors that could be categorized as roadway characteristics, environmental characteristics, crash characteristics, temporal characteristics, vehicle characteristics and driver characteristics significantly influencing adverse weather-related crash injury outcomes. Additionally, the temporal stability and space transferability of the models were investigated through a series of likelihood ratio tests. Marginal effects were also adopted to analyze the spatiotemporal stability of the explanatory variables. The findings exhibited an overall spatiotemporal instability while some indicators were also observed to be of relative spatial or temporal stability such as insurance, overturning, proceeding and early morning over the four-year period considered. This paper provided some immediate recommendations targeted at preventing crashes under adverse weather conditions across different regions and could potentially facilitate the development of crash injury mitigation policies. More regions could be considered to provide observations for spatial instability tests in future research.

恶劣天气可能会增加驾驶错误和危险驾驶行为的可能性，有必要明确了解与恶劣天气相关的决定因素如何影响碰撞伤害严重程度的内生和外生机制，并探索其时空稳定性。为了研究与恶劣天气相关的碰撞严重程度决定因素的异质性和时空稳定性，本文估计了两组均值和方差具有异质性的随机参数多项式logit模型。使用俄亥俄州和加利福尼亚州的碰撞数据在 2013 年 1 月 1 日至 2016 年 12 月 31 日期间。 根据可归类为道路特征的多种因素，调查了三种碰撞伤害严重程度类别，包括无伤害、轻伤和重伤，环境特征、碰撞特征、时间特征、车辆特征和驾驶员特征显着影响与恶劣天气相关的碰撞伤害结果。此外，通过一系列似然比测试研究了模型的时间稳定性和空间可转移性。边际效应也被用来分析解释变量的时空稳定性。调查结果显示出整体时空不稳定，同时还观察到一些指标具有相对的空间或时间稳定性，例如在所考虑的四年期间的保险、翻车、诉讼和清晨。本文提供了一些即时建议​​，旨在防止不同地区在恶劣天气条件下发生碰撞，并可能促进碰撞伤害减轻政策的制定。在未来的研究中，可以考虑更多的区域为空间不稳定性测试提供观测。