Assessing the Operational Safety of New Energy Truck Platoons Under Information Uncertainty and Longitudinal Slope

Autonomous truck platooning represents a transformative advancement in modern highway logistics, offering substantial benefits in fuel efficiency and traffic throughput. However, the practical deployment of such systems is frequently compromised by sensing limitations and environmental factors, particularly localization uncertainty and varying longitudinal road slopes. In this study, the desired safety margin (DSM) model is employed to systematically investigate how these variables jointly affect platoon‐level string stability and the safety performance of car‐following maneuvers. Through rigorous linear stability analysis, we derived a novel stability criterion that explicitly accounts for stochastic localization errors and road geometry parameters. The findings reveal a critical trade‐off: a negative uncertainty value, indicating a conservative distance estimation, significantly expands the stable region, thereby reinforcing platoon stability and mitigating the likelihood of rear‐end collisions. Conversely, with positive uncertainty, the stability region is reduced, while dynamic performance is improved by shortening the system’s response time to lead‐vehicle maneuvers. Furthermore, although the longitudinal slope has a negligible impact on fundamental stability characteristics, it exerts a decisive influence on operational safety due to the gravity‐induced longitudinal acceleration component. Consequently, the results indicate that constraining randomly varying uncertainty within a calibrated range, together with slope‐aware control, can optimize the balance between stability and responsiveness, offering valuable theoretical guidance for robust control design in next‐generation autonomous heavy‐duty vehicles.