Integrated LTV-MPC Collision Avoidance of Autonomous Tractor Semi-trailers in Emergency Scenarios.

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)(2023)

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Abstract
In recent years, autonomous tractor semi-trailers have been considered a promising solution for improving safety and efficiency in transportation. However, due to the complicated dynamics characteristics of the tractor semi-trailer, collision avoidance trajectory planning and tracking control are still challenges. Especially in emergency scenarios, the tractor semi-trailer needs to maneuver close to its handling limits to avoid sudden obstacles, which may lead to a high risk of instability. This paper develops a linear time-varying model predictive control (LTV-MPC) based collision avoidance framework that integrates trajectory planning and tracking control for autonomous tractor semi-trailers. Compared with the current research, the proposed controller, incorporating the detailed vehicle dynamics, coordinates lateral and longitudinal control simultaneously, which can extend the vehicle dynamics boundary and enhance controller performance in critical conditions. Moreover, the developed convex collision avoidance constraints guarantee that the proposed MPC problem can be recast as a quadratic programming (QP) problem, which reduces the computational complexity. The simulation results in Simulink-TruckMaker demonstrate the effectiveness of the proposed approach.
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Key words
Emergency Scenarios,Model Predictive Control,Quadratic Programming,Vehicle Dynamics,Trajectory Planning,Quadratic Programming Problem,Risk Of Instability,Longitudinal Control,Lateral Control,Trajectory Tracking Control,Active Control,Joint Angles,System Input,Perceptual System,Lateral Force,Vehicle Position,Obstacle Avoidance,Reference Trajectory,Slack Variables,Vertical Load,Lateral Tyre Forces,Front Axle,Road Boundary,Steering Angle,Sideslip Angle,Joint Point,Rear Axle,Vehicle Stability,Safety Constraints,Tyre Forces
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