Indirect Shared Control for Cooperative Driving Between Driver and Automation in Steer-by-Wire Vehicles
Indirect Shared Control for Cooperative Driving Between Driver and Automation in Steer-by-Wire Vehicles
复制标题
线控车辆驾驶员与自动化协同驾驶的间接共享控制
DOI：
10.1109/tits.2020.3010620
复制
发表时间：
2021-12-01
影响因子：
8.5
通讯作者：
Cheng, Bo
中科院分区：
文献类型：
--
作者：
Li, Renjie;Li, Yanan;Cheng, Bo
人们普遍认为，在自动车辆完全满足现实世界的操作条件之前，驾驶员应该保持在控制回路中。提出了一种用于线控车辆的“间接共享控制”框架，该框架允许驾驶员和自动驾驶之间通过加权输入和方法不断地共享控制权。提出了一种用于间接共享控制的基于模型预测控制(MPC)的“最佳响应”驾驶员转向模型。与任何传统的手动驾驶驾驶员模型不同，该模型假定驾驶员可以学习控制器策略并将其合并到其内部模型中以进行预测路径跟踪。提供了驾驶员模型的解析解，以实现离线仿真。通过驾驶模拟器实验，验证了间接共享控制系统在高速公路车道保持任务中的优势。结果表明，所提出的间接共享控制方法能有效地提高受试者的车道保持性能，减少转向控制工作量。所提出的驾驶员转向模型也得到了实验数据的验证，其预测误差小于传统的MPC驾驶员模型。
It is widely acknowledged that drivers should remain in the control loop before automated vehicles completely meet real-world operational conditions. This paper presents an "indirect shared control" framework for steer-by-wire vehicles, which allows the control authority to be continuously shared between the driver and automation through an weighted-input-summation method. A "best-response" driver steering model based on model predictive control (MPC) for indirect shared control is proposed. Unlike any conventional driver model for manual driving, this model assumes that drivers can learn and incorporate the controller strategy into their internal model for predictive path following. The analytic solution to the driver model is provided to enable off-line simulations. A driving-simulator experiment was conducted to demonstrate the advantages of the indirect shared control system in a highway lane-keeping task. The result showed that the proposed indirect shared control method was effective to improve the subjects' lane-keeping performance and reduce steering control effort. The proposed driver steering model was also validated by the experiment data, which produced a smaller prediction error than the conventional MPC driver model.