首页|General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

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This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the gener-ated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajec-tories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers'behavior and summarizing their manipulation characteris-tics of"seeking benefits and avoiding losses."Finally,by integrating the idea of receding-horizon opti-mization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework's feasibility and effective-ness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers'manipulation.

Autonomous vehicleTrajectory planningMulti-performance objectivesPrinciple of least action

Heye Huang、Yicong Liu、Jinxin Liu、Qisong Yang、Jianqiang Wang、David Abbink、Arkady Zgonnikov

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School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China

Department of Cognitive Robotics,Faculty of Mechanical,Maritime and Materials Engineering(3mE),Delft University of Technology,Delft 2628,Netherlands

Department of Software Technology,Faculty of Electrical Engineering,Mathematics and Computer Science,Delft University of Technology,Delft 2628,Netherlands

Xi'an Institute of High-Technology,Xi'an 710051,China

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National Natural Science Foundation of China(the Key Project)Science Fund for Creative Research Groups国家留学基金委项目Joint Laboratory for Internet of VehiclesMinistry of Education-China MOBILE Communications Corporation

5213120152221005

2024

10.1016/j.eng.2023.10.001

工程(英文)

工程(英文)

CSTPCDEI
ISSN：2095-8099
年,卷(期)：2024.33(2)
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