Trust-Based Control and Scheduling for UGV Platoon under Cyber Attacks 2019-01-1077
Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors. To deal with inaccurate information due to a V2C cyber attack, a RoboTrust algorithm is designed to analyze vehicle trustworthiness and eliminate information with low credit. Finally, a human operator scheduling algorithm is proposed when the number of abnormal UGVs exceeds the limit of what human operators can handle concurrently. Representative simulation results demonstrate that the proposed automated decision aid can effectively guide human operators when working with platoons under cyber attacks. The platoon survivability has been improved by the proposed algorithm when compared to those that operate without this system.
Citation: Li, F., Mikulski, D., Wagner, J., and Wang, Y., "Trust-Based Control and Scheduling for UGV Platoon under Cyber Attacks," SAE Technical Paper 2019-01-1077, 2019, https://doi.org/10.4271/2019-01-1077. Download Citation
Author(s):
Fangjian Li, Dariusz Mikulski, John R. Wagner, Yue Wang
Affiliated:
Clemson University, U.S. Army TARDEC
Pages: 10
Event:
WCX SAE World Congress Experience
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Unmanned ground vehicles
Data management
Cybersecurity
Control systems
Vehicle to vehicle (V2V)
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