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Deep reinforcement learning-based drift parking control of automated vehicles

Science China(Technological Sciences) 2023年第4期66卷 1152-1165页

作者： LENG Bo YU YiZe LIU Ming CAO Lei YANG Xing XIONG Lu School of Automotive Studies Tongji University

Drift parking usually requires precise control of a vehicle by a professional driver,which can reflect the performance of the vehicle under critical conditions.The obstacles to implementing this action include the high coupling between the longitudinal and lateral states,the high precision required for the vehicle initial state when the drift is triggered,and the difficulty in determining the reference state variables in the drift process.A two-segment drift parking control system is proposed in this paper.In the approaching control segment,the vehicle achieves the drift-triggered vehicle speed and pose,which relies on a pathtracking algorithm based on linear time-varying model predictive control.In the drifting control segment,the deep reinforcement learning algorithm twin-delayed deep deterministic policy gradient is creatively introduced to the controller design.It solves the precise vehicle motion control problem under the condition of the rear wheels having locked brakes.Through various simulations,the superiority and robustness to different initial conditions and abrupt changes in the parking space are verified.The effectiveness of the proposed control system is verified by a ground test.

关键词： automated vehicles deep reinforcement learning drifting control vehicle dynamics control

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Post-Impact Motion Planning and Tracking control for Autonomous vehicles

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Chinese Journal of Mechanical Engineering 2022年第5期35卷 315-332页

作者： Cong Wang Zhenpo Wang Lei Zhang Huilong Yu Dongpu Cao National Engineering Research Center for Electric vehicles Beijing Institute of TechnologyBeijing 100081China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China School of vehicle and Mobility Tsinghua UniversityBeijing 100080China

There is an increasing awareness of the need to reduce traffic accidents and fatality due to vehicle collision.Post-impact hazards can be more serious as the driver may fail to maintain effective control after collisions.To avoid subsequent crash events and to stabilize the vehicle,this paper proposes a post-impact motion planning and stability control method for autonomous vehicles.An enabling motion planning method is proposed for post-impact situations by combining the polynomial curve and artificial potential field while considering obstacle avoidance.A hierarchical controller that consists of an upper and a lower controller is then developed to track the planned motion.In the upper controller,a time-varying linear quadratic regulator is presented to calculate the desired generalized forces.In the lower controller,a nonlinear-optimization-based torque allocation algorithm is proposed to optimally coordinate the actuators to realize the desired generalized forces.The proposed scheme is verified under comprehensive driving scenarios through hardware-in-loop tests.

关键词： Active safety Post-impact control Motion planning vehicle dynamics control

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Coordinated control Architecture for Motion Management in ADAS Systems

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 432-444页

作者： Tzu-Chi Lin Siyuan Ji Charles E. Dickerson David Battersby the wolfson school of mechanical electrical and manufacturing engineeringloughborough universityLoughhoroughLE11 3TUUK jaguar land rover GaydonCV35 0RRUK ieee

Advanced driver assistance systems(ADAS) seek to provide drivers and passengers of automotive vehicles increased safety and comfort. Original equipment manufacturers are integrating and developing systems for distance keeping, lane keeping and changing and other functionalities. The modern automobile is a complex system of systems. How the functionalities of advanced driver assistance are implemented and coordinated across the systems of the vehicle is generally not made available to the wider research community by the developers and manufactures. This paper seeks to begin filling this gap by assembling open source physics models of the vehicle dynamics and ADAS command models. Additionally, in order to facilitate ADAS development and testing without having access to the details of ADAS, a coordinated control architecture for motion management is also proposed for distributing ADAS motion control commands over vehicle systems. The architecture is demonstrated in a case study where motion is coordinated between the steering and the braking systems, which are typically used only for a single functionality. The integrated vehicle and system dynamics using the coordinated control architecture are simulated for various driving tasks. It is seen that improved trajectory following can be achieved by the proposed coordinated control architecture. The models, simulations and control architecture are made available for open access.

关键词： Coordinated system feed-forward and feedback control integration control modeling and simulation tire modeling vehicle modeling vehicle dynamics control

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