基于改进的驾驶风险领域,对无人驾驶汽车的本地路径规划进行研究
Pan Liu1, Yongqiang Chang2, Jianping Gao2
1College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, 471000, Henan, China. ziliupan@126.com.
Scientific reports
|November 25, 2024
概括
本研究引入了一种改进的风险场模型,用于无人驾驶汽车运动规划. 改进的车型通过考虑车辆尺寸和方向,确保更安全,更顺的轨迹,提高驾驶稳定性.
科学领域:
- 机器人技术和自主系统
- 人工智能的人工智能
- 车辆动力学 车辆动力学
背景情况:
- 无人驾驶汽车的运动规划至关重要,现场理论被广泛用于驾驶安全评估.
- 现有的风险场模型缺乏准确性,无法考虑车辆尺寸和方向约束.
研究的目的:
- 为自动驾驶汽车运动规划开发一个改进的风险场模型.
- 通过结合车辆尺寸和行驶方向来解决当前车型的局限性.
- 在不同的驾驶场景中解决局部最小问题.
主要方法:
- 开发了一个新的风险场模型,包括机动车辆,道路和行人风险场.
- 为当地最低限度问题提出解决方案.
- 使用MATLAB验证的模拟和使用Prescan和MATLAB/Simulink进行的共同模拟.
主要成果:
- 与传统方法相比,改进的场理论算法产生了更平滑的轨迹.
- 观察到方向角,曲率和滚动角度的波动幅度有显著的减少.
- 提高了驾驶稳定性,实现了更顺的目标点.
结论:
- 拟议的风险场模型提高了自动驾驶汽车运动规划的准确性和安全性.
- 改进的算法在轨道平滑性和稳定性方面提供了卓越的性能.
- 证明了用于更安全的自主导航的重大应用潜力.
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