Adverse weather poses a significant threat to the serviceability of highway infrastructure, as it causes more frequent and severe crash incidents. This study focuses on evaluating the resilience of highway networks by examining the crash-induced safety impact in response to extreme weather events. Unlike traditional service drop-based methods for resilience evaluation, this study endeavors to evaluate highway resilience in a spatial context. Three spatial metrics, including K-nearest neighbors, proximity to highways, and Kernel density hot spot, are introduced and employed to compare and analyze the spatial patterns (magnitude and distribution) of crashes in pre- and post-weather conditions. An illustrative example is also provided to showcase the applications of the proposed spatial resilience metrics for two study areas in the State of Illinois, U.S. The contribution of this study is to provide transportation practitioners with a tool to evaluate highway spatial resilience both visually and quantitatively, and ultimately improve highway safety and operation.

中文翻译：

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评估恶劣天气条件下公路网的空间弹性

恶劣天气对高速公路基础设施的可维护性构成了重大威胁，因为它导致更频繁，更严重的撞车事故。这项研究的重点是通过检查撞车事故对极端天气事件的安全影响来评估公路网的弹性。与传统的基于服务下降的弹性评估方法不同，本研究致力于在空间环境下评估高速公路的弹性。引入了三个空间量度，包括K近邻，靠近高速公路和内核密度热点，以比较和分析天气前和天气后碰撞的空间模式（幅度和分布）。还提供了一个说明性示例，以展示提议的空间弹性指标在伊利诺伊州两个研究区域中的应用，