Vulnerable road users (VRUs) such as pedestrians and bicyclists, also known as non-motorists, are vulnerable due to lack of protection in traffic. They are even more vulnerable at intersections due to increased exposure and conflicts with motor vehicles whose paths have to cross each other. The main objective of this thesis study was to determine factors that contribute significantly to the crash severity of intersection-related crashes involving motor vehicles and the vulnerable road users. When a motor vehicle crashes with a non-motorist road user, the non-motorist road user sustains the higher injury levels. Based on the objectives of this study, a three-year crash database from January 2013 to December 2015 acquired from the Ohio Department of Public Safety was utilized for this analysis. The logistic stepwise selection procedure was applied to estimate statistically significant predictor variables that contribute to increasing bicyclist and pedestrian-related crash severity levels. The logistic regression model identified five statistically significant predictor variables out of fourteen independent variables considered in the current research. The predictors that increase the crash severity of crashes involving VRUs who collide with vehicles at intersections are pedestrian-related, road contour, gender, light condition, and unit in error. The other factors that are usually significant such as posted speed limits, alcohol-related, gender, age, etc., were not significant in the current study. However, speed-related was not tested in the current study due to lack of enough cases where speeding was reported as contributing factor in the data set used.

This guide is intended to provide information on how to identify safety and mobility needs for pedestrians with the roadway right-of-way. Useful for engineers, planners, safety professionals and decision-makers, the guide covers such topics as: the Walking Environment including sidewalks, curb ramps, crosswalks, roadway lighting and pedestrian over and under passes; Roadway Design including bicycle lanes, roadway narrowing, reducing the number of lanes, one-way/two-way streets, right-turn slip lanes and raised medians; Intersections with roundabouts, T-intersections and median barriers; and Traffic calming designs.

The purpose of this research was to apply the basic National Highway Traffic Safety Administration (NHTSA) pedestrian and bicyclist typologies to a sample of recent crashes and to refine and update the crash type distributions with particular attention to roadway and locational factors. Five thousand pedestrian-motor vehicle crashes and 3,000 bicycle-motor vehicle crashes were coded in a population-based sample drawn from the states of California, Florida, Maryland, Minnesota, North Carolina, and Utah. Future safety considerations should be systemwide and include an examination of intersections and other junctions, well designed facilities, and increased awareness of pedestrians and bicyclists by motor vehicle drivers.

Pedestrians and bicyclists are the most vulnerable road users and suffer the most severe consequences when crashes take place. An extensive literature is available for crash severity in terms of driver safety, but fewer studies have explored non-motorized users' crash severity. Furthermore, most research efforts have examined pedestrian and bicyclist crash severity in urban areas. This study focuses on state roads (mostly outside major urban areas) and aims to identify contributing risk factors of fatal and severe crashes involving pedestrians and bicyclists in state roads. Two ordinal regression models were developed (one for pedestrian and the other for bicyclist crashes) to examine crash severity risk factors. Additional models were developed to investigate road and traffic characteristics that could increase the likelihood of fatal crashes. In the model for pedestrian crash severity risk factors such as age, vehicle type and movement, light conditions, road classification, traffic control device, posted speed limit, location of the pedestrian and wet road surface during clear weather conditions are statistically significant. The bicyclist crash severity model indicates that age, crash location, vehicle movement and alcohol intoxication during dark conditions are statistically significant. In terms of road characteristics and traffic conditions, the models suggested risk factors such as arterials, light conditions, posted speed limit, roadways, and high heavy vehicle volume, increased the odds of a crash being fatal. The results seem to suggest that besides improvements in roadway characteristics, additional countermeasures to reduce crash severity for vulnerable users should include separation of vulnerable users from traffic, educational campaigns, more strict control of alcohol intoxicated drivers, and protection strategies of senior pedestrians.