Stochastic simulation of an adaptive cruise control (ACC) system in electric vehicles to investigate human perceptions of safety, consistency, and comfort

OBJECTIVE: This study evaluates and compares the performance of adaptive cruise control (ACC) systems in an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using stochastic simulation, based on measures of safety, consistency, and comfort. METHODS: The safety, consistency and comfort measures were mapped to ACC system performance measures such as spacing distance and acceleration. Next, a high-fidelity and validated ACC simulation model was adapted to create two ACC systems: One system, called ACC-EV system, was composed of an EV automatically following an ICEV, and the other system, called ACC-ICEV system, was composed of an ICEV automatically following an ICEV. In addition, two scenarios were developed to evaluate whether and how much the three measures might be different between the two ACC systems. The first scenario simulated an extreme deceleration event, and the second scenario represented a repeated stop-and-go traffic event. RESULTS: < 0.001 for all measures. In addition, the magnitude of the differences between the ACC-EV system and the ACC-ICEV system was substantially higher for the extreme deceleration event scenario than for the repeated stop-and-go traffic event scenario across all three measures. CONCLUSIONS: We were able to show corroborating evidence that ACC-EV system can provide safer, more stable, and more comfortable driving behavior compared to those of the ACC-ICEV system for the two distinctive scenarios. Furthermore, the results imply that a human driver using the ACC-EV system might feel less stressed and require less cognitive effort to maintain constant vigilance due to the enhanced safety, consistency, and comfort, contributing to traffic accident prevention.