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作 者:赵克刚[1] 曾润林 梁志豪[1] 钟浩龙 ZHAO Ke-gang;ZENG Run-lin;LIANG Zhi-hao;ZHONG Hao-long(School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510641,China)
机构地区:[1]华南理工大学机械与汽车工程学院,广州510641
出 处:《科学技术与工程》2024年第17期7376-7386,共11页Science Technology and Engineering
基 金:广东省重点领域研发计划(2019B090912001)。
摘 要:在泊车空间狭窄的条件下,现有的基于混合A^(*)算法的泊车路径规划存在成功率低或规划速度慢等问题,为了解决这一问题,设计了一种改进混合A^(*)路径规划算法。通过将圆弧样条曲线作为参考路径,并以参考路径上的点作为混合A^(*)算法的目标点,进而搜索出成功泊入车库的路径。根据不同车位宽度进行了基于MATLAB的批量仿真测试,结果表明:改进后的混合A^(*)算法能够显著提高车辆在特定区域泊入车库的成功率,同时具有一定的规划效率。最后基于Prescan、Carsim和Simulink进行了联合仿真实验,验证了所设计算法规划的路径满足实车实验的跟踪要求。Under the condition of narrow parking space,problems such as low success rate or slow planning speed are encountered in the existing parking path planning based on the hybrid A^(*) algorithm.In order to solve the problems,an improved hybrid A^(*) path planning algorithm was designed.By using the arc spline as the reference path and using the points on the reference path as the target point of the hybrid A^(*) algorithm,the path to successfully park into the garage was searched.Batch simulation tests based on MATLAB were conducted according to different parking space widths.The results show that a significant improvement in the success rate of vehicles parking into the garage in a specific area can be achieved by the improved hybrid A^(*) algorithm,and at the same time,a certain level of planning efficiency was attained.Finally,a joint simulation experiment was conducted based on Prescan,Carsim and Simulink,which verifies that the tracking requirement of the real vehicle experiment is met by the path planned by the designed algorithm.
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