Improving driver yielding to pedestrians at crosswalks may help prevent pedestrian fatalities, which have increased over the last decade in the United States. The level of assertiveness exhibited by pedestrians when they arrive at a crosswalk may have a significant impact on driver yielding behavior, but assertiveness is not defined clearly or studied thoroughly in the literature. This study defined three levels of pedestrian assertiveness and collected naturalistic video data at two uncontrolled crosswalks in Madison and Milwaukee, Wisconsin to explore the relationship between pedestrian assertiveness and driver yielding behavior. Driver yielding rates were 71% for pedestrians exhibiting Level 1 (high), 30% for Level 2 (moderate), and 3% for Level 3 (low) assertiveness. The pedestrian assertiveness definitions were also used to assess the potential impact of a high-visibility enforcement (HVE) program in the communities where the study took place. Observations taken after the HVE program showed a significantly higher rate of driver yielding to pedestrians exhibiting a moderate level of assertiveness. This result is promising, since a moderate level of assertiveness may be reasonable for pedestrians to adopt, especially if supported by educational messages for pedestrians to clearly indicate their intent to cross within a crosswalk. This exploratory study provides a framework for future analysis and highlights the need for additional research on the relationship between pedestrian assertiveness and driver yielding behavior.
A significant portion of crashes occurred on highway segments, with more than 90% of crashes associated with driving errors. To avoid a crash, a driver needs to detect a hazard, decide the safest driving maneuvers, and execute them properly. Driver errors at any of these sequential phases may lead to a crash; therefore, it is necessary to identify the contributing factors and assess their influence on driver behavior. To assist this investigation, a multinomial probit model was employed to study driver errors reported in crashes in rural and urban areas. The modeling results identified many highway geometric features, traffic conditions, roadway events, and driver characteristics as statistically correlated to different types of driver error. Following the extensive list, the impacts of error-contributing factors were discussed within each error category. This exercise helps to gain a better understanding of similar or varying effects of explanatory variables across different error categories. The broad and insightful information will help researchers and safety professionals to better understand when, where, and how the driver error may lead to a crash and to develop cost-effective preventive countermeasures.
One of the most common circumstances contributing to pedestrian crashes is drivers failing to yield to pedestrians in crosswalks. A better understanding of driver yielding behavior can help identify optimal safety treatments to improve driver yielding and prevent pedestrian injuries and fatalities. Recognizing this need, this study observed driver yielding behavior at 20 uncontrolled intersections along two-lane arterial and collector roadways with posted speed limits of 25 or 30 miles per hour in Milwaukee, Wisconsin during weekday afternoon peak travel periods in fall 2016. The naturalistic observations showed that drivers yielded 60 times out of 364 opportunities when the pedestrian wished to cross (16% driver yielding rate). Yielding rates differed between intersections, ranging from a high of 60% to a low of 0%. A binary logistic model showed that drivers were more likely to yield to pedestrians when the major roadway had a lower speed limit or less traffic; when the intersection had a shorter crossing distance or a bus stop; and when the pedestrian was White, standing in the street, or acting assertively. Finally, all else equal, intersections with no reported pedestrian crashes in the last 5 years had higher driver yielding rates than intersections with at least two reported pedestrian crashes. While this exploratory study is based on a small sample of observations, it supports several engineering, education, and enforcement strategies and provides suggestions for future studies of driver yielding behavior.
Pedestrian and bicycle crashes have been increasing at an alarming pace in recent years. Between 2009 and 2016, annual U.S. pedestrian fatalities increased 46%, and bicyclist fatalities increased 34%. Crashes involving pedestrians and bicyclists, or vulnerable road users (VRUs), are negatively correlated with roadway factors, and positively correlated with environmental and socioeconomic factors. However, specific variables representing these factors are often correlated, making it difficult to accurately characterize relationships between individual variables and pedestrian and bicyclist safety. This study used the structural equation model technique to overcome this problem. Pedestrian and bicyclist crash frequency and more than 60 explanatory variables for 200 highway corridors in Wisconsin were collected. The interrelationships between observed “manifest” variables and unobserved “latent” variables were tested. The results suggest that the most important latent variables influencing the crash frequency of VRUs are bicycle/pedestrian-oriented roadway design (e.g., paved shoulders, sidewalks, and bike lanes), exposure (e.g., walking and biking activity, and employment density), and low social status (e.g., educational level, and wage percentage). The benefits of this study may help community planners, transportation researchers, and policymakers with a better understanding of the intricate interrelationship of the influential factors contributing to VRUs road crashes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.