In recent years, the rapid advancement of autonomous driving and intelligent connected vehicle technologies has significantly accelerated the development and deployment of Advanced Driver Assistance Systems (ADAS). Among them, Adaptive Cruise Control (ACC) plays a central role by automatically regulating inter-vehicle distance and longitudinal speed, thereby improving both driving safety and ride comfort. However, most existing commercial ACC systems still rely on a small set of predefined, discrete time gap values (e.g., 1.0 s, 1.5 s, 2.0 s), which lack adaptability to varying traffic conditions, driver intent, and road types. This rigidity limits the system’s ability to achieve an optimal trade-off among multiple performance objectives.