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Review analyzes control technologies and challenges for autonomous tractor-trailer systems in off-road environments, highlighting areas for future research.
The path-tracking and motion control of autonomous tractor–trailer systems (TTSs) in unstructured off-road environments have become important research topics of intelligent equipment. Traditional control architectures face challenges due to multiple physical constraints such as time-varying soil rheology, time-varying wheel slip, multi-body nonlinear coupling, and vehicle stability constraints. This review provides an overview of advanced control technologies for autonomous TTSs in off-road environments. First, this review analyzes multi-source sensors and joint state estimation frameworks for time-varying terrain classification, all-wheel slip ratio estimation, and articulation angle. Secondly, nonholonomic kinematic, multi-body three-dimensional spatial dynamic, and tire–soil interaction mechanic models are deconstructed for on-axle and off-axle hitching configurations. On this basis, adaptive kinematic control, model predictive control (MPC), robust disturbance rejection, and distributed electric-drive control strategies are compared horizontally, and the application of active trailer steering, torque vectoring, and implemented chassis cooperative control in active safety is elaborated. Finally, emerging research directions, including online tire–soil interaction learning, embodied AI foundation models, and V2X-enabled multi-vehicle cooperative platooning, are discussed to provide insights into the development of next-generation fully autonomous off-road tractor–trailer systems.
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Song et al. (2026) studied this question.
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