An analysis of pedestrian crash trends and contributing factors in Texas. (September 2021)

• Record Type: Journal Article
• Authors: Bernhardt, Maxwell; Kockelman, Kara
• Is Part Of: Journal of transport & health. Volume 22(2021)
• Publication Date: 2021-09
• Subjects: Pedestrian crashes -- Pedestrian fatalities -- Road safety -- Crash countermeasures -- Homelessness -- Texas traffic; Transportation -- Health aspects -- Periodicals; Transportation -- Periodicals; Public Health -- Periodicals; Noise, Transportation -- Periodicals; Air Pollutants -- Periodicals; 388
• DOI: 10.1016/j.jth.2021.101090
• Languages: English
• ISSNs: 2214-1405

Abstract

Abstract: Introduction & research objectives: Pedestrian crash rates and deaths have risen across the United States over the past decade, in contrast to motor vehicle traffic crash counts and rates. Analysis of pedestrian crash rates per vehicle-mile traveled and walk-mile traveled (VMT and WMT) illuminates the impacts of homelessness, land development densities, income, weather, and many other variables across the State of Texas, helping to propel more effective safety policies. Methods: This study examines key factors for and countermeasures against pedestrian crashes, while predicting pedestrian crash rates per VMT and WMT, as sourced from the Texas DOT (TxDOT) and the 2017 National Household Travel Survey (NHTS) add-on sample. Crash data from TxDOT's Crash Records Information System (CRIS) database were analyzed using an ordinary least-squares (OLS) regression by controlling for a variety of socioeconomic, climate, and roadway design variables, including homelessness, which has emerged as a serious issue along freeway rights-of-way in many U.S. urban areas. Results: At the county level in Texas, there is a moderately positive relationship between job density and pedestrian crash rates, but a practically significant and negative relationship with population density. Median income and homelessness have very practically significant, positive impacts on pedestrian crash and fatality rates. For example, a 1 standard deviation increase in homelessness per 1000 residents is associated with a +14.4% of 1 standard deviation rise in the total pedestrian crash rate per WMT at the county level, all else constant. Similarly, pedestrian crashes per WMT rise in a notable way with the share of children under age 17 and rates of homelessness. Conclusions: These results suggest significant positive relationships between pedestrian crash rates per VMT and per WMT with respect to household incomes and homelessness, at the county level. Pedestrian crashes and pedestrian deaths per WMT also reveal practically significant contributions by larger youth populations and poverty rates. A weaker but still practically significant relationship exists between crash rates per VMT and population growth rate, warranting further investigation on the relationship between exurban land use patterns and pedestrian crashes. Highlights: OLS regression of Texas pedestrian crash data at the county level. Interaction between prevalence of homelessness and pedestrian crash rates. Diverse social, economic and environmental factors effects on pedestrian safety. Time of day, year effects on pedestrian crashes and fatalities. Exhaustive literature review of pedestrian safety research.