Radar-Only Cooperative Adaptive Cruise Control Under Acceleration Disturbances: ACC, KF-CACC, and Multi-Q IMM-KF CACC

Abstract

The rapid increase in global vehicle usage has intensified challenges such as traffic congestion, frequent accidents, and energy consumption, highlighting the need for safe and efficient platooning strategies. Conventional adaptive cruise control (ACC), while widely adopted, suffers from string instability that amplifies disturbances along a platoon. Communication-based cooperative ACC (CACC) can theoretically guarantee string stability at short headways, but its dependence on costly and unreliable vehicle-to-vehicle (V2V) links limits large-scale deployment. Radar-only CACC using single-model Kalman Filter (KF) alleviates this dependency, yet its estimation accuracy degrades under abrupt maneuvers due to model mismatch. To overcome these limitations, this paper proposes a Multi-Q Interacting Multiple Model Kalman Filter (Multi-Q IMM-KF) approach that adaptively blends multiple motion models to ensure robust acceleration estimation across diverse driving conditions. A four-vehicle platoon simulation in CarSim-Simulink demonstrates that the Multi-Q IMM-KF CACC significantly reduces spacing error propagation and improves velocity tracking compared with ACC and Nominal KF-CACC, offering a cost-effective and communication-resilient solution for practical platoon control.