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连接和自动化车辆排队合作控制与测量错误的建模和优化
Weiming Luo1, Xu Li1, Jinchao Hu1
1School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Sensors (Basel, Switzerland)
|November 14, 2023
概括
本研究引入了连接和自动化车辆 (CAV) 排队的合作控制方法,以克服传感器错误. 卡尔曼波器有效地减轻了测量不准确性,确保了稳定和舒适的排队.
科学领域:
- 控制系统工程 控制系统工程
- 机器人技术 机器人技术 机器人技术
- 运输系统 运输系统
背景情况:
- 连接和自动驾驶汽车 (CAV) 提供了更高的交通效率和安全.
- 合并,一个关键的CAV应用程序,面临稳定性挑战,由于传感器测量错误.
- 保持中队稳定性需要强大的控制策略,考虑到传感器噪音.
研究的目的:
- 开发一种合作的控制方法,用于对传感器测量错误进行稳健的CAV排队.
- 分析传感器错误叠加对排队稳定的影响.
- 确保稳定,舒适和高效的协调车辆跟踪行为.
主要方法:
- 制定CAV排队系统的状态空间方程,包括传感器测量误差.
- 对传感器测量误差叠加效应的统计分析.
- 应用卡尔曼波器以减轻测量误差.
- 将形成控制问题转化为最佳控制决策问题.
主要成果:
- 拟议的卡尔曼波器有效地减轻了传感器测量错误的不良影响.
- 合作控制方法使协调的车辆跟踪行为成为可能.
- 在整个排中实现了平稳的加速和减速.
- 消除了交通波动,提高了排队的稳定性.
结论:
- 开发的合作控制方法确保了CAV排队的稳定性和舒适性.
- 该方法有效地解决了传感器测量错误,这是CAV系统的一个关键挑战.
- 模拟结果使用现实世界的车辆轨迹数据验证了该方法的性能.
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