Analysis of Advanced Driver-Assistance Systems in Police Vehicles (TTI-05-02)

Project Description: Motor vehicle crashes are the leading cause of deaths for police officers. These crashes have been mainly attributed to the use of in-vehicle technologies while driving. Advanced driver-assistance systems (ADAS) have the potential to improve officer safety by removing some of driver vehicle control responsibilities. The objective of this project was to evaluate ADAS in police vehicles. This project included two phases including (1) ADAS needs and implementation analysis in police vehicles; and (2) evaluation of police ADAS in a driving simulation study. The first phase included a systematic review of literature and an online survey with officers to understand their ADAS needs and current systems in police vehicles. The second phase evaluated ADAS in high-demand situations using a high-fidelity driving simulator. Results indicated that officer behavior and opinion on ADAS features were influenced by the trust officers had in the available ADAS systems among other key factors such as ADAS training and perceived usefulness. ADAS features including forward collision warning (FCW), automatic emergency braking (AEB), and blind spot monitoring (BSM) had positive effect on police officers' driving performance and reducing workload. The outcomes of this project provided regarding effective ADAS features/types and can improve officer safety in police operations. Data Scope: Phase 1 Number of observations: 73 observations Type of data: Combination of categorical, binary, and continuous data types. The data were collected through an online demographic questionnaire and an online survey. Phase 2 Number of observations: 398 observations. 23 driving performance data were removed due to participants not following the instructions, 34 brake reaction time data points were removed when participants who did not follow the instructions when negotiating hazards, 7 data points were removed due to crashes, and 12 data points were removed from the secondary task time data due to participants not paying attention to the question. For blink rate and percentage change in pupil size measures, data were removed (identified with “NA” in the dataset) in cases where the eye-tracking glasses failed or the data did not meet the confidence level defined by the manufacturer. Type of data: Combination of categorical, binary, and continuous data types. Data Specification: Please see Data Specification document.