Impact Analysis of Surrounding Vehicle Behavior on Autonomous Truck Platooning

The development of e-commerce logistics has driven the expansion of truck transportation. The application of cooperative adaptive cruise control (CACC) technology in truck platooning is considered as an effective way to improve safety and road capacity, as well as reduce fuel consumption and environmental pollution. However, the influence of surrounding vehicles on the safety and efficiency of truck platoons remains a challenge in mixed traffic. This study aims to evaluate the impact of surrounding vehicle behavior, such as car-following and cut-in, on the performance of autonomous truck platooning. Considering traffic flow stability and the impact of the actual road environment, the intelligent driver model is improved. The CACC system control algorithm is further designed. Meanwhile, human-driven vehicle behavior is described based on the full velocity difference model. A simulation platform integrating MATLAB/Simulink/PreScan is developed to replicate real-world vehicle interactions. The safety and efficiency of truck platooning are analyzed quantitatively considering multiple factors. The results show that two car-following events and two cut-in events reduce the fuel saving rate of the platoon by 0.52%–5.04% and 0.15%–2.00%, respectively. At high velocity, the collision risk reflected by inverse time-to-collision is higher for gaps in the front of the platoon as a result of car-following and cut-in. Shorter headway times can result in higher fuel consumption and lower safety. Four recommendations to reduce the impact of surrounding vehicles are presented based on the findings to support the successful deployment of truck platooning in mixed traffic.