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◆ IEEE Transactions on Automation Science and Engineering2026-01-01· Trajectory

MCTP: A Multi-Coupled Dynamics Trajectory Planning Scheme for Autonomous Driving in Extreme Conditions

XuePeng Hu, Yu Zhang, Chengye Wang, Shi Shaoyang, Zhenfeng Wang, Yechen Qin

原始摘要(英文原文)· Original abstract
Trajectory planning is essential for ensuring the safe operation of autonomous vehicles. However, existing methods rarely consider the vehicle’s multi-coupled dynamics, including lateral-longitudinal motion coupling, tire force coupling, and lateral instability. This omission can result in infeasible trajectories, vehicle instability, or even accidents under extreme conditions. To address this challenge, this study presents a multi-coupled dynamics trajectory planning (MCTP) scheme. MCTP establishes a coupled kinematics model to accurately represent vehicle motion states and constructs a tire force representation model, which based solely on vehicle motion states, facilitating seamless integration into trajectory planning. By incorporating coupled tire force characteristics and lateral stability analysis, a set of coupled dynamic constraints is formulated to ensure trajectory feasibility and lateral stability. Additionally, a multi-objective function is designed to further optimize trajectory safety, dynamic feasibility, and lateral stability, with the optimal trajectory obtained through receding horizon optimization. Closed-loop validation on both hardware-in-the-loop and real-vehicle experimental platforms demonstrates that, MCTP generates trajectories with enhanced safety and feasibility. It also improves tracking stability margins and dynamics performance, highlighting its effectiveness in handling extreme conditions.
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