Advancing Crash Investigation with Connected and Automated Vehicle Data: Insights from a Survey of Law Enforcement

Some of the 6 million plus police-reported crashes in the US require detailed investigations. As connected and automated vehicles (CAVs) gain popularity and are also involved in crashes, new data from CAVs can be used to improve the accuracy of crash investigations. In addition to information from Event Data Recorders, CAV data on vehicle trajectories and pre-crash conditions can enhance the understanding of causation factors. This study investigates how CAV data can advance crash investigations by answering research questions about what pertinent information is lacking in crash investigations and how law enforcement can use CAV data. This study addresses these questions by performing a survey of 61 law enforcement officials working in crash investigations in the state of Tennessee. The survey included respondents’ vehicle crash investigation experience, training exposure, and familiarity with automated vehicle technologies. The survey showed that respondents have previous experience working with video camera footage in crash investigations, and responses indicate that camera footage would provide the most helpful new information when investigating a crash. The survey also revealed law enforcement officials’ moderate familiarity with lidar and low familiarity with millimeter-wave radar and ultrasound sensors. Survey respondents also indicated that data such as vehicle trajectories made available through automated vehicle sensors would be useful during crash investigations. The survey revealed a need for standardization in CAV data retrieval and training processes. It resulted in a list of pertinent training topics for law enforcement that prioritizes a thorough understanding of CAV technology and data retrieval processes.