Dark lighting conditions, including those occurring at dawn and dusk, are correlated with increased nonmotorist crash frequency owing to reduced visibility, but little research has been done that investigates the spatial relationship between roadway lights and nonmotorist crashes on a community scale. This research used kernel density estimation methods to calculate the commonalities between geolocated streetlight data and non-motorist-vehicle crashes from 2010 to 2018 in Cambridge, Massachusetts. It was observed that dawn, dusk, and darkness showed a significant correlation between nonmotorist crashes and the absence of roadway lighting, all exceeding the control analysis undertaken with crashes occurring in daylight. The Getis-Ord ${\mathrm{G}}_i^{*}$ hot spot cluster analysis indicated that areas with the greatest density of streetlights were associated with fewer nonmotorist crash hot spots. Future research seeks to corroborate these findings with data from other cities and to assess roadway lighting as a facet of pedestrian network connectivity.

由于能见度降低，黑暗的照明条件（包括发生在黎明和黄昏的那些）与非驾驶者碰撞频率的增加相关，但很少有研究在社区范围内调查道路灯与非驾驶者碰撞之间的空间关系。该研究使用核密度估计方法来计算 2010 年至 2018 年在马萨诸塞州剑桥的地理定位路灯数据与非机动车碰撞事故之间的共性。据观察，黎明、黄昏和黑暗显示出非机动车碰撞与缺乏道路照明之间的显着相关性，所有这些都超过了对发生在白天的碰撞进行的控制分析。Getis-Ord${\mathrm{G}}_{\mathrm{一世}}^{*}$热点聚类分析表明，路灯密度最大的区域与较少的非机动车碰撞热点相关。未来的研究旨在用其他城市的数据证实这些发现，并将道路照明作为行人网络连通性的一个方面进行评估。