Prior Exposure,Warning Algorithm Parameters and Driver Response to Imminent Rear-End Collisions on a High-Sfideltiy Simulator

Abstract

Rear-end collisions account for over 25% of crashes. Because driver inattention is a contributing factor in more than 60% of these collisions, rear-end collision avoidance systems (RECAS) offer a promising approach to reduce crashes and save lives. This study uses a high-fidelity driving simulator to examine driver response to imminent rear-end collision situations and address two issues. First, the study examines how variations in algorithm parameters affect RECAS effectiveness. The results show an early warning helps drivers react more quickly and avoid more collisions, providing critical data for tradeoff studies of RECAS parameters and nuisance alarm rates. Second, the study investigates how drivers respond to a second collision scenario shortly after their first exposure. The results show drivers react more quickly to the second exposure and avoid more collisions, but that the effect of the second exposure does not interact with other experimental variables or change the fundamental response dynamics. This suggests that multiple exposures to imminent crash situations can generate useful data, forming the basis for more efficient experimental designs of simulator-based studies.

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