Trust-Based Control and Scheduling for UGV Platoon under Cyber Attacks
Published April 2, 2019 by SAE International in United States
Downloadable datasets for this paper availableAnnotation of this paper is available
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.
CitationLi, 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.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
- Ogawa H., Miyazaki Y., Yoshida S., and Sasaki S., “System for Automatically Controlling Movement of Unmanned Vehicle and Method Therefor,” U.S. Patent 4,716,530, Dec. 29, 1987.
- Dey, K.C., Yan, L., Wang, X., Wang, Y. et al., “A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC),” IEEE Transactions on Intelligent Transportation Systems 17(2):491-509, 2016.
- Naus, G.J., Vugts, R.P., Ploeg, J., van de Molengraft, M.J., and Steinbuch, M., “String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach,” IEEE Transactions on Vehicular Technology 59(9):4268-4279, 2010.
- Pajic, M., Weimer, J., Bezzo, N., Tabuada, P. et al., “Robustness of Attack-Resilient State Estimators,” in ACM/IEEE 5th International Conference on Cyber-Physical Systems, Berlin, Germany, IEEE Computer Society, Apr. 2014, 163-174.
- Teixeira, A., Sandberg, H., and Johansson, K.H., “Networked Control Systems under Cyber Attacks with Applications to Power Networks,” in American Control Conference (ACC), Maryland, IEEE, June 2010, 3690-3696.
- Biron, Z.A., Dey, S., and Pisu, P., “Real-Time Detection and Estimation of Denial of Service Attack in Connected Vehicle Systems,” IEEE Transactions on Intelligent Transportation Systems (99):1-10, 2018.
- Heredia, G., Caballero, F., Maza, I., Merino, L. et al., “Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors,” Sensors 9(9):7566-7579, 2009.
- Jin, Y., Minai, A.A., and Polycarpou, M.M., “Cooperative Real-Time Search and Task Allocation in UAV Teams,” in Proceedings of 42nd IEEE Conference on Decision and Control, Maui, HI, vol. 1, IEEE, Dec. 2003, 7-12.
- Hu, H., Lu, R., Zhang, Z., and Shao, J., “Replace: A Reliable Trust-Based Platoon Service Recommendation Scheme in Vanet,” IEEE Transactions on Vehicular Technology 66(2):1786-1797, 2017.
- Li, Z., Filev, D.P., Kolmanovsky, I., Atkins, E. et al., “A New Clustering Algorithm for Processing GPS-Based Road Anomaly Reports with a Mahalanobis Distance,” IEEE Transactions on Intelligent Transportation Systems 18(7):1980-1988, 2017.
- Setter, T., Gasparri, A., and Egerstedt, M., “Trust in Multi-Agent Networks: From Self-Centered to Team-Oriented,” in American Control Conference, Seattle, WA, May 2017.
- Mikulski, D.G. and Karlsen, R.E., “Trust-Based Learning and Behaviors for Convoy Obstacle Avoidance,” in Unmanned Systems Technology XVII, Vol. 9468, International Society for Optics and Photonics, 2015, 94680L.
- Cummings, M.L., Bruni, S., and Mitchell, P.J., “Human Supervisory Control Challenges in Network-Centric Operations,” Reviews of Human Factors and Ergonomics 6(1):34-78, 2010.
- Goodrich, M.A., Schultz, A.C. et al., “Human-Robot Interaction: A Survey,” Foundations and Trends® in Human-Computer Interaction 1(3):203-275, 2008.
- Chen, J.Y. and Barnes, M.J., “Human-Agent Teaming for Multirobot Control: A Review of Human Factors Issues,” IEEE Transactions on Human-Machine Systems 44(1):13-29, 2014.
- Chen, J.Y., Barnes, M.J., and Qu, Z., “Roboleader: An Agent for Supervisory Control of Multiple Robots,” in Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction, Osaka, Japan, IEEE, Mar. 2010, 81-82.
- Mikulski D. G., “Trust-Based Cooperative Games and Control Strategies for Autonomous Military Convoys,” Army Tank Automotive Research Development and Engineering Center, Warren, MI, Tech. Rep., 2013.
- Isermann, R., “Model-Based Fault-Detection and Diagnosis-Status and Applications,” Annual Reviews in control 29(1):71-85, 2005.
- Chou, P.B.-L., Iyer, B.S., Lai, J., Levas, A. et al., “System and Method for Vehicle Diagnostics and Health Monitoring,” U.S. Patent 6,330,499, Dec. 11, 2001.
- Lei, C., Van Eenennaam, E., Wolterink, W.K., Karagiannis, G. et al., “Impact of Packet Loss on CACC String Stability Performance,” in 2011 11th International Conference on ITS Telecommunications (ITST), Petersburg, Russia, IEEE, Aug. 2011, 381-386.
- Koscher, K., Czeskis, A., Roesner, F., Patel, S. et al., “Experimental Security Analysis of a Modern Automobile,” in 2010 IEEE Symposium on Security and Privacy (SP), Berkeley, CA, IEEE, May 2010, 447-462.
- Liu, Y., Ning, P., and Reiter, M.K., “False Data Injection Attacks against State Estimation in Electric Power Grids,” ACM Transactions on Information and System Security (TISSEC) 14(1):13, 2011.
- Han, G., Jiang, J., Sun, N., and Shu, L., “Secure Communication for Underwater Acoustic Sensor Networks,” IEEE Communications Magazine 53(8):54-60, 2015.
- Wood, A.D. and Stankovic, J.A., “Denial of Service in Sensor Networks,” Computer 35(10):54-62, 2002.
- Chen, J. and Patton, R.J., Robust Model-Based Fault Diagnosis for Dynamic Systems. Vol. 3 (Springer Science & Business Media, 2012).
- Altman, D., Machin, D., Bryant, T., and Gardner, M., Statistics with Confidence: Confidence Intervals and Statistical Guidelines (John Wiley & Sons, 2013).
- Zheng, D., Leung, J., and Lee, B., “Online Update of Model State and Parameters of a Monte Carlo Atmospheric Dispersion Model by Using Ensemble Kalman Filter,” Atmospheric Environment 43(12):2005-2011, 2009.
- Lee, D. and Spong, M.W., “Passive Bilateral Teleoperation with Constant Time Delay,” IEEE Transactions on Robotics 22(2):269-281, 2006.