Comfort Optimization of Adaptive Cruise Control Based on Heart Rate Variability and Fuzzy Control

Abstract

This paper investigated the impact of braking intensity of self-driving cars at different initial speeds on straight road sections on drivers’ comfort, with a view to achieving the comfort optimization of adaptive cruise control (ACC). Specifically, the real vehicle test was conducted in an enclosed venue based on the within-subjects design of 3 × 3 × 2, and the data pertaining to electrocardiogram (ECG) and subjective evaluation of 9 subject drivers in 9 sub tests were collected. Besides, the impacts of different motion states on heart rate variability (HRV) parameters were analyzed using the general linear model for repeated measures, and the relationships among drivers’ comfort, decelerations, and standard deviation of NN intervals (SDNN, an index of HRV) were obtained based on subjective and objective analyses. Additionally, a control strategy based on HRV and fuzzy control was formulated to realize the comfort optimization of ACC in case of an abrupt deceleration of the preceding vehicle, the verifications were performed through joint simulation. The results exhibited that the control strategy based on HRV and fuzzy control could shorten the deceleration time in case of an abrupt deceleration of the preceding vehicle, and may improve the comfort in such scenario.