Stackelberg Game-based Control Method for Driver-automation Collaboration in Ship Remote-control

被引：0
|
作者：
Li C. [1 ,2 ,3 ]
Yan X. [1 ,3 ,4 ]
Liu J. [1 ,3 ,4 ]
Huang Y. [1 ,3 ,4 ]
Li S. [1 ,2 ]
机构：
[1] State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan
[2] School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan
[3] National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan
[4] Intelligent Transport System Research Center, Wuhan University of Technology, Wuhan
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2024年 / 24卷 / 03期
基金：
中国国家自然科学基金;
关键词：
control authority adjustment; driver-automation collaboration; model predictive; shared steering control; ship remote-control; waterway transportation;
D O I：
10.16097/j.cnki.1009-6744.2024.03.003
中图分类号：
学科分类号：
摘要：
To solve the problem of human-machine control objective non-consistency in the ship remote-control process, this paper proposes a shared steering control method within the Stackelberg framework and considers the human-dominated and machine-auxiliary operating mode of the system. The human-machine interaction in ship collision avoidance collaborative steering task is described as a non-cooperative game relationship under complete information conditions. By constructing the state space of the driver and the co-pilot controller, the differential strategy is derived for Stackelberg game, and the uniqueness and existence of Nash equilibrium solution is proved with Fan-Glicksberg fixed points theorem. Based on model predictive control method, the trajectory tracking controller is designed with pre-allocating driving weight for different driving style and maneuvering skills, rolling and optimization in a finite time domain through feedback correction. And the control authority will be adjusted online in combination of the safety navigation boundary, collision risk and degree of human-machine conflicts. Taking the lateral displacement and driver's operational load as evaluation indexes, the effectiveness of method is verified in inland maneuvering scenarios. Simulation results show that the proposed method could provide personalized assistance for remote operators with different driving styles and maneuvering skills, while there exists intention conflict between the driver and the co-pilot controller, it can adjust the pre-allocated weight in accordance with the navigating risk dynamically, so as to make the ship motion more compliant with driver's maneuvering intentions under the premise of ensuring navigating safety. © 2024 Science Press. All rights reserved.
引用
收藏
页码：21 / 31and74
页数：3153
相关论文
共 18 条
  • [1] YAN X P, LI C, LIU J L., Architecture and key technologies for new generation of waterborne transportation system, Journal of Transportation Systems Engineering and Information Technology, 21, 5, pp. 22-29, (2021)
  • [2] FENG L, WILTSCHE C, HUMPHREY L, Et al., Synthesis of human-in-the-loop control protocols for autonomous systems, IEEE Transactions on Automation Science and Engineering, 13, 2, pp. 450-462, (2016)
  • [3] ZHENG N, LIU Z, REN P, Et al., Hybrid-augmented intelligence: Collaboration and cognition, Frontiers of Information Technology & Electronic Engineering, 18, 2, pp. 153-179, (2017)
  • [4] DEMIR M, MCNEESE N J, GORMAN J C, Et al., Exploration of teammate trust and interaction dynam ICS in human-autonomy teaming, IEEE Transactions on Human-machine Systems, 51, 6, pp. 696-705, (2021)
  • [5] MONARCH R M., Human-in-the-loop machine learning: Active learning and annotation for human-centered AI, (2021)
  • [6] YE P, WANG X, ZHENG W, Et al., Parallel cognition: Hybrid intelligence for human-machine interaction and management, Frontiers of Information Technology & Electronic Engineering, 23, 12, pp. 1765-1779, (2022)
  • [7] WANG Y H, LIU W., A situation cognition model based on human-machine hybrid fusion, Journal of Command and Control, 9, 1, pp. 76-84, (2023)
  • [8] ZHANG X W, XIE L, CHU X M, Et al., An overview of path following control methods for unmanned surface vehicles, Journal of Transport Information and Safety, 38, 1, pp. 20-26, (2020)
  • [9] LAZCANO A M R, NIU T, AKUTAIN X C, Et al., MPC-based haptic shared steering system: A driver modeling approach for symbiotic driving, IEEE/ASME Transactions on Mechatronics, 26, 3, pp. 1201-1211, (2021)
  • [10] LI C, CHEN Y H, ZHAO H, Et al., Stackelberg game theory-based optimization of high-order robust control for fuzzy dynamical systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52, 2, pp. 1254-1265, (2020)
12