ROITP:Road Obstacle-Involved Trajectory Planner for Autonomous Trucks  

作　　者：Yechen Qin Yiwei Huang Wenhao Yu Hong Wang 

机构地区：[1]School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China [2]Scool of Vehicle and Mobility,Tsinghua University,Beijing 100084,China

出　　处：《Chinese Journal of Mechanical Engineering》2025年第1期340-352,共13页中国机械工程学报(英文版)

基　　金：Supported by National Natural Science Foundation of China (Grant Nos. 52072215, 52221005, 52272386);Beijing Municipal Natrual Science Foundation (Grant No. L243025);National Key R&D Program of China (Grant No. 2022YFB2503003);State Key Laboratory of Intelligent Green Vehicle and Mobility;fundamental Research Funds for the Central Universities

摘　　要：Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation.However,their maximum speed and ability to navigate a variety of driving conditions,particularly uneven roads,are limited by a high center of gravity,which increases the risk of rollover.Road bulges,sinkholes,and unexpected debris all present additional challenges for autonomous trucks’operational design,which current perception and decisionmaking algorithms often overlook.To mitigate rollover risks and improve adaptability to damaged roads,this paper presents a novel Road Obstacle-Involved Trajectory Planner(ROITP).The planner categorizes road obstacles using a learning-based algorithm.A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics.Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.

关 键 词：Autonomous truck Trajectory planning Obstacle avoiding Vehicle stability Polynomial curves 

分 类 号：U469.7[机械工程—车辆工程] U463.6[交通运输工程—载运工具运用工程]