Exploring Temporal and Manufacturer-Specific Trends of Automated Vehicle Crashes Using Sequence of Events

The present study uses Crash Sequence Analysis to identify automated vehicles (AV) crash patterns and evaluate the temporal (2014 to 2023) and manufacturer-specific (Cruise or Waymo) trends in these patterns. This method builds upon the evaluation of crash scenarios by considering the sequential nature of crashes, incorporating crash progression and contributing factors. The results highlight the current challenge faced by manufacturers in designing systems that are safe yet perform in a manner expected by human drivers. The proportional reduction of crash patterns involving rear-end collisions during left or right turns suggests that actions were taken by manufacturers to address the aforementioned challenge. However, other crash patterns have shown a proportional increase in recent years, such as collisions with objects and on narrow roads, with specific variations by manufacturers. These findings provide key insights for shaping future AV development, guiding public sector decisions, and building public trust in automation.