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基于复杂驾驶场景的模型预测理论的动态轨迹规划研究
Hongluo Li1, Hai Pang2, Hongyang Xia1
1School of Automobile and Transportation Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
本研究引入了一种使用模型预测控制 (MPC) 进行自动驾驶的新动态变车道轨迹规划方法. 该方法确保在复杂的驾驶场景中实时适应性.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 交通运输的人工智能
- 汽车工程 汽车工程
背景情况:
- 自动驾驶在很大程度上依赖于轨迹规划,以确保安全和高效的导航.
- 当前的轨道规划方法在动态驾驶场景中面临挑战,实时环境变化.
- 动态变化车道对于在复杂交通中运行的自动驾驶汽车至关重要.
研究的目的:
- 为自动驾驶汽车提出一种新的动态变车道轨迹规划方法.
- 解决现有方法在实时,动态驾驶环境中的局限性.
- 提高自动驾驶系统的性能和安全性.
主要方法:
- 开发了主机车辆和周围车辆的动力模型.
- 应用模型预测控制 (MPC) 理论,包括预测模型,目标函数和约束.
- 采用最小正方形配合方法来生成可适应的车道更换轨迹.
主要成果:
- 提出的方法在动态驾驶场景中表现出了卓越的实时适应性.
- 模拟研究验证了轨道规划方法的有效性.
- 该方法成功地为动态车道变化生成了最佳控制序列.
结论:
- 新的动态变车道轨迹规划方法为自动驾驶提供了强大的解决方案.
- 这项研究有助于开发能够实现全场景运行的自动驾驶汽车.
- 这些发现为在复杂环境中更安全,更有效的自主导航铺平了道路.
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