Using SHRP2 NDS data to examine infrastructure and other factors contributing to older driver crashes during left turns at signalized intersections

Abstract

Drivers age 65 and over have higher rates of crashes and crash-related fatalities than other adult drivers and are especially over-represented in crashes during left turns at intersections. This research investigated the use of SHRP2 Naturalistic Driving Study (NDS) data to assess infrastructure and other factors contributing to left turn crashes at signalized intersections, and how to improve older driver safety during such turns. NDS data for trips involving signalized intersections and crash or near-crash events were obtained for two driver age groups: drivers age 65 and over (older drivers) and a sample of drivers age 30−49, along with NDS pre-screening and questionnaire data. Video scoring of all trips was performed to collect additional information on intersection and trip conditions. To identify the most influential factors of crash risk during left turns at signalized intersections, machine learning and regression models were used. The results found that in the obtained NDS dataset, there was a relatively small volume of crashes during left turns at signalized intersections. Further, model results found the statistically significant variables of crash risk for older drivers were associated more with health and cognitive factors rather than the infrastructure or design of the intersections. The results suggest that a study using only SHRP2 NDS data will not lead to definitive findings or recommendations for infrastructure changes to increase safety for older drivers at signalized intersections and during left turns. Moreover, the findings of this study indicates the need to consider other data sources and data collection methods to address this critical literature gap in older driver safety.