Abstract
During the process of reverse parking, it is difficult to achieve the ideal reference trajectory while avoiding collision. In this study, with the aim of establishing reference trajectory optimization for automatic reverse parking that smooths and shortens the trajectory length and ensures the berthing inclination angle is small enough, an improved immune moth–flame optimization method based on gene correction is proposed. Specifically, based on the standard automatic parking plane system, a reasonable high-quality reference trajectory optimization model for automatic parking is constructed by combining the cubic spline-fitting method and a boundary-crossing solution based on gene correction integrated into moth–flame optimization. To enhance the model’s global optimization performance, nonlinear decline strategies, including crossover and variation probability and weight coefficient, and a high-quality solution-set maintenance mechanism based on fusion distance are also designed. Taking garage No.160 of the Dalian Shell Museum located in Dalian, Xinghai Square, as the experimental site, experiments on automatic parking reference trajectory optimization and tracking control were carried out. The results show that the proposed optimization algorithm provides higher accuracy for reference trajectory optimization and can achieve better tracking control of the reference trajectory.
Funding Information
  • National Natural Science Foundation of China (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • General Project of Natural Science Foundation of Inner Mongolia (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • Basic scientific research business expenses of colleges and universities directly under Inner Mongolia Autonomous Region - Plan to Improve the Scientific Research and Innovation Ability of Young Teachers (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • Inner Mongolia Minzu University (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • Liaoning Provincial Department of Transportation Scientific Research Project (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)
  • Liaoning Provincial Department of Education Scientific Research Project (62341313, 2023MS06013, NJYT-17-B34, GXKY22125, BS416, 202344, JYTMS20230038)

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