基于混合A*和NMPC的狭窄空间的自动停车轨迹规划
Pei Zhang1,2, SiLong Zhou1,2, Jie Hu3,4
1Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology), Wuhan, 430070, People's Republic of China.
Scientific reports
|January 8, 2025
概括
本研究介绍了城市环境的先进自动停车轨迹规划方法. 这种方法优化了车辆在狭窄空间中的路径,提高了效率和安全性.
科学领域:
- 机器人技术和自主系统
- 城市规划和交通工程 城市规划和交通工程
背景情况:
- 城市化和车辆所有权的增加造成了重大的城市停车挑战.
- 需要在狭窄区域提供高效,安全和空间优化的自动化停车解决方案.
研究的目的:
- 开发一种流,舒适和适应性的自动停车轨迹规划方法.
- 优化空间利用,提高交通流量,减少城市停车场场景中的事故风险.
主要方法:
- 混合A*算法用于初始路径生成.
- 立方多项式适用于速度和加速度配置文件.
- 结合非线性模型预测控制 (NMPC) 用于轨迹优化,考虑动力学和避障限制.
主要成果:
- 与基本的混合A*算法相比,优化的轨迹显示出更高的空间利用率.
- 实现了增强的轨迹流性和舒适性.
- 在狭窄空间内的自动化停车任务中展示了有效的性能.
结论:
- 拟议的基于NMPC的轨迹规划方法为在受限制的城市环境中自动化停车提供了有效的解决方案.
- 该方法在效率,安全和空间优化方面取得了显著的改进.
- 在未来的自动驾驶系统中具有广泛应用的潜力.
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