Infrastructure Deficiency Correlation with Pedestrian/Cyclist Crashes: A Data-Driven Approach

A model for identifying the impacts of infrastructure deficiency on road traffic safety is needed to help governments prioritize strategic investments to increase public safety. During the 2010-2019 period, U.S. pedestrian and cyclist fatalities rose by 44% and 36%, respectively, and previous studies have shown a positive correlation between pedestrian/cyclist crashes and low-income areas. To our knowledge, this study is the first to investigate further the reasons behind the higher probability of pedestrian and cyclist crashes in low-income areas. The proposed hypothesis is that the higher probability of pedestrian and cyclist crashes in low-income areas correlates with higher infrastructure deficiencies such as sidewalk, crosswalk, and pavement deficiencies. Ordered logistic regression and K-means clustering techniques have been used in this study to model the impacts of infrastructure deficiency on pedestrian-vehicle and cyclist-vehicle crash frequency at intersections in Dallas, Texas as a case study. The results show that for intersections in low-income areas, the odds of having pedestrian and cyclist crashes are 22% and 34% higher than intersections in middle-income and high-income areas, respectively. For intersections with sidewalk, crosswalk, or pavement deficiencies, the odds of having pedestrian and cyclist crashes are 86%, 15%, and 29% higher, respectively, than intersections without such deficiencies. For intersections with one, two, or three infrastructure deficiencies, the odds of having pedestrian and cyclist crashes are 2.8, 3.0, and 3.2 times higher, respectively, than intersections without infrastructure deficiencies