Balancing safety and efficiency: Control strategy for car-following scenarios considering uncertain factors

How to enhance driving safety and traffic efficiency while achieve the balancing between them remains a fundamental question in designing car-following control strategy. In this work, an interval-based safety distance model and a coordinated optimization framework for car-following behavior are presented. First, to improve driving safety, three typical uncertain factors are analyzed, and a car-following safety distance model that considers these factors is established using interval mathematics. Then, an optimal control framework for car-following behavior is constructed. By integrating the safety distance model with the car-following control model, a balanced control that can enhance both safety and efficiency is achieved. Additionally, to improve comfort and safety during car-following, two car-following control strategies are developed: (1) a dual-mode switching control strategy and (2) a near-optimal feedback control strategy. Finally, to improve computational efficiency, we introduce a novel numerical optimization method that combines a local-global adaptive solving strategy with a node-recycling mechanism. The effectiveness of the proposed control methods is validated through numerical simulations.