Horizontal curve segments are locations of critical safety concern given their high crash rates. Extensive research has identified that behavioral factors influence the occurrence of such crashes. However, the most beneficial countermeasure for a curve is not always implemented or is implemented inefficiently due to a lack of full understanding of driver behavior at curves compared to tangent roadway segments. The aim of this research is to identify the conditions that impact safety at curve locations compared to tangent segment locations. This is completed through a literature review of current research relating to curve safety issues and a safety analysis of curve and tangent segment data using a novel dataset that includes curve data throughout a region. The results of this study revealed several factors that cause horizontal curves to have a higher crash rate related to driver performance, including the increased task load and demand required at curve segments compared to tangent segments, and that horizontal curve segments have an increased rate of crashes per mile with an increasing AADT compared to tangent segments. Further, horizontal curve segments along one-way operations are of increased safety concern for drivers compared to tangent segments and two-way operations. The results of this study present the conditions that can be more carefully considered in future studies and analyses to consider the human factor cause behind the increased safety issue at curve segments.

No abstract

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 [Formula: see text] 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.