自动驾驶汽车的新控制模型使用了基于模型预测和斯坦利控制器的集成
Mustafa Hamid Al-Jumaili1,2, Yasa Ekşioğlu Özok3
1Electrical and Computer Engineering Department, Altinbas University, Istanbul, Turkey. malju2@unh.newhaven.edu.
Scientific reports
|August 27, 2024
概括
一个新的基于Model Predictive和Stanley的控制器 (MPS) 增强了自动驾驶汽车的控制. 这种混合系统集成了两个控制器,以提高性能和减少各种驾驶场景中的错误.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 自动驾驶汽车技术自动驾驶汽车技术
背景情况:
- 自动驾驶汽车需要强大的控制系统,以确保安全高效的运行.
- 现有的控制方法,如模型预测控制和斯坦利控制,有个人的局限性.
研究的目的:
- 为自动驾驶汽车应用引入一种新的混合控制系统,即基于模型预测和斯坦利的控制器 (MPS).
- 利用模型预测和斯坦利控制器的优势来克服个别缺点.
主要方法:
- 开发一个混合控制系统,集成模型预测和斯坦利控制器.
- 在各种场景中测试MPS控制器的路径跟踪和整体车辆控制.
- 在直线和曲线路段进行评估.
主要成果:
- 在各种自动驾驶场景中,MPS控制器表现出高性能和灵活性.
- 混合方法有效地结合了组成控制者的优势.
- 对比分析表明,MPS系统的性能优于现有的控制方法.
结论:
- 拟议的MPS控制器为自动驾驶汽车控制提供了一个强大而高性能的解决方案.
- 这种混合战略代表了自动驾驶控制系统的重大进步.
- 该MPS控制器的适应性使其适合复杂和多样化的驾驶条件.
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