Advancing crash investigation with connected and automated vehicle data: Insights from a survey of law enforcement

With over six million annual police-reported crashes in the United States, surveys on law enforcement’s involvement in crash investigations are rare. A unique and innovative survey is designed in the study to address the contemporary issues of vehicle automation, focusing on the integration of Connected and Automated Vehicles (CAVs) data to advance crash investigation accuracy. Utilizing both descriptive statistics and rigorous factor analysis, the study surveyed 61 Tennessee law enforcement officers with crash investigation duties. The survey included respondents’ vehicle crash investigation experience, training exposure, and familiarity with automated vehicle technologies. The study’s results indicate that officers have experience utilizing video camera footage in crash investigations. The findings revealed law enforcement officers’ moderate awareness of LiDAR and limited understanding of millimeter-wave radar and ultrasound sensors. Survey respondents acknowledged that access to vehicle trajectory data from CAV sensors could significantly aid crash investigations. The survey assessed the law enforcement needs for standardized CAV data retrieval and identified critical training areas, emphasizing a comprehensive grasp of CAV technologies and data processes. The study establishes the foundation for a customized training program, emphasizing the critical need for law enforcement to keep pace with rapidly advancing vehicular technologies in the realm of crash investigation.