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ICTD 2025

Transportation Safety

POSTER RECEPTION (View list of posters here)

Older Driver Crash Patterns Across Signalized, Stop, and Yield-Controlled Intersections

Tuesday, June 10, 2025
4:45 PM – 6:00 PM MT
Abstract: In the United States, the increase in the older population (65 and older) is considered one of the most significant demographic trends in this decade, which led to a rise in the number of older licensed drivers. This study addresses the gap in the existing literature by investigating the critical patterns and associations among factors contributing to older driver crashes at signalized, stop-controlled, and yield-controlled intersections in Louisiana using Association Rules Mining (ARM). The findings reveal distinct risk factors for fatal-severe and other injury crashes at these intersections. Fatal-severe crashes at signalized and stop-controlled intersections are most likely to occur at night and often involve pedestrians or single-vehicle crashes. Crashes on stop-controlled intersections in dark no-streetlight conditions have more severe consequences, whereas for signalized intersections, fatal-severe crashes mostly happen in the dark with continuous streetlight conditions. On the contrary, other injury crashes tend to happen during the day in clear weather, frequently involving rear-end collisions and inattentive older drivers. The yield-controlled intersections present unique challenges for older drivers during daytime and weekdays, with prevalent right-angle and left-turn collisions. The results of this study highlight the need for targeted safety countermeasures to mitigate the older driver crash risk at intersections, providing valuable insights for traffic safety professionals and decision-makers.

Learning Objectives:

Attendees can expect to learn the following from this session:
  • Upon completion, participants will be able to list the critical crash patterns of older driver crashes at signalized, stop-controlled, and yield-controlled intersections.
  • Upon completion, participants will be able to describe the process of applying Association Rules Mining (ARM) to analyze crash data.
  • Upon completion, participants will be able to identify the safety countermeasures for mitigating older driver crash risks at intersections.