Enhancing Traditional Adaptive Cruise Control through Map-Based Feature Integration: A Performance evaluation Study on Stationary Vehicle Response at High Speeds

Adaptive Cruise Control (ACC) has become a widely adopted driver-assist technology, designed primarily to regulate a vehicle’s longitudinal movement while maintaining a safe following distance from the preceding vehicle. A key performance criterion is the system’s ability to detect and respond to both moving and stationary target vehicles within the ego vehicle’s path. While manufacturers typically validate ACC performance within specific speed ranges, responding to stationary objects remains particularly challenging due to limited sensor range, difficulty in detecting distant stationary targets, and constrained deceleration capabilities. Beyond certified operating limits, overall system reliability may degrade. Nonetheless, increasing industry and regulatory expectations are driving the need to extend ACC functionality across wider and more clearly defined speed domains. Modern ACC systems are further evolving to recognize and respond to various road features, including traffic lights, stop signs, intersections, curved road segments, and roundabouts—an expanding set of scenarios enabled by multi-sensor fusion and map integration using standard definition (SD) and high definition (HD) maps. Regulatory frameworks are increasingly addressing these map-based functionalities. This paper investigates the interaction between map-based functionalities and traditional ACC behavior, specifically examining how map integration enhances ACC responsiveness to critical scenarios. Due to the wide variety of possible cases, this study focuses on stationary vehicle encounters, recognized as the most challenging and safety-critical scenario, particularly at higher speeds. Simulation studies are conducted to evaluate the impact of map-based augmentation on ACC performance, with results demonstrating performance improvements, and extended operational capability beyond conventional speed limits.