Dynamic Weights Leading Cruise Control: Design and Analysis for Connected and Automated Vehicles in Mixed Platoons under Time-Varying Delays

The increasing presence of connected and automated vehicles (CAVs) with vehicle-to-vehicle communication capabilities presents substantial opportunities to enhance traffic flow efficiency and safety. When CAVs operate within mixed platoons alongside human-driven vehicles (HDVs), time-varying communication delays, incomplete car following dynamics modeling, and unpredictable human driving behaviors can destabilize traffic flow and diminish automation benefits. This paper proposes a dynamic weights leading cruise control (DWLCC) framework that adaptively balances delayed and real-time information by dynamically adjusting feedback weights based on communication conditions. The controller is theoretically analyzed using HDV dynamics and validated through simulations with full nonlinear car-following models. A comprehensive stability analysis framework examines the combined influence of time-varying delays, communication range constraints, and control parameters. Using Lyapunov-Krasovskii methods and head-to-tail string stability analysis, explicit stability boundaries are analytically derived, providing practical guidelines for robust controller design. Extensive numerical simulations validate the proposed approach under diverse operating conditions. Compared with conventional fixed-weight methods, DWLCC demonstrates superior velocity tracking and spacing regulation, enhanced safety margins, and reduced fuel consumption. These results highlight the potential of adaptive, delay-aware control strategies for safe and efficient CAV deployment in heterogeneous traffic environments.