Abstract
To improve the cybersecurity of flocking control for connected and automated vehicles (CAVs), this paper proposes a novel resilient flocking control by specifically considering cyber-attack threats on vehicle tracking errors. Using the vehicle tracking error dynamics model, a dual extended Kalman filter (DEKF) is applied to detect cyber-attacks as an unknown constant on vehicle tracking information with noise rejections. To handle the coupling effects between tracking errors and cyber-attacks, the proposed DEKF consists of a tracking error filter (TEF) and a cyber-attack filter (CAF), which are utilized to conduct the prediction and correction of tracking errors alternatively. Whenever an abnormal tracking error is detected, an observer-based resilient flocking control is enabled. Demonstrated by simulation results, the proposed cyber-attack detection method and resilient flocking control design can successfully achieve and maintain the flocking control of multi-CAV systems by rejecting certain cyber-attack threats.
References
1.
National Highway Traffic Safety Administration’s National Center for Statistics and Analysis
, 2016
, “2015 Motor Vehicle Crashes: Overview
,” U.S. Department of Transportation, August
2016
. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812318, Accessed April 2018.2.
Chen
, B.
, and Cheng
, H. H.
, 2010
, “A Review of the Applications of Agent Technology in Traffic and Transportation Systems
,” IEEE Trans. Intell. Transp. Syst.
, 11
(2
), pp. 485
–497
. 10.1109/TITS.2010.20483133.
Murray
, R. M.
, 2007
, “Recent Research in Cooperative Control of Multivehicle Systems
,” ASME J. Dyn. Syst. Meas. Control
, 129
(5
), pp. 571
–583
. 10.1115/1.27667214.
Parkinson
, S.
, Ward
, P.
, Wilson
, K.
, and Miller
, J.
, 2017
, “Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges
,” IEEE Trans. Intell. Transp. Syst.
, 18
(11
), pp. 2898
–2915
. 10.1109/TITS.2017.26659685.
Siegel
, J. E.
, Erb
, D. C.
, and Sarma
, S. E.
, 2017
, “A Survey of the Connected Vehicle Landscape–Architectures, Enabling Technologies, Applications, and Development Areas
,” IEEE Trans. Intell. Transp. Syst.
, 19
(8
), pp. 2391
–2406
. 10.1109/TITS.2017.27494596.
Biron
, Z. A.
, Dey
, S.
, and Pisu
, P.
, 2018
, “Real-time Detection and Estimation of Denial of Service Attack in Connected Vehicle Systems
,” IEEE Trans. Intell. Transp. Syst.
, 19
(12
), pp. 3893
–3902
. 10.1109/TITS.2018.27914847.
Rahman
, M. S.
, Mahmud
, M. A.
, Oo
, A. M. T.
, and Pota
, H. R.
, 2016
, “Multi-agent Approach for Enhancing Security of Protection Schemes in Cyber-Physical Energy Systems
,” IEEE Trans. Industrial Informatics
, 13
(2
), pp. 436
–447
. 10.1109/TII.2016.26126458.
Zhu
, M.
, and Martinez
, S.
, 2013
, “On the Performance Analysis of Resilient Networked Control Systems Under Replay Attacks
,” IEEE Trans. Automatic Control
, 59
(3
), pp. 804
–808
. 10.1109/TAC.2013.22798969.
Boem
, F.
, Gallo
, A. J.
, Ferrari-Trecate
, G.
, and Parisini
, T.
, “A Distributed Attack Detection Method for Multi-Agent Systems Governed by Consensus-Based Control
,” Proc. of 2017 IEEE 56th Annual Conf. on Decision and Control
, Melbourne, VIC, Australia
, Dec. 2017
, pp. 5961
–5966
.10.
Arrichiello
, F.
, Marino
, A.
, and Pierri
, F.
, 2015
, “Observer-based Decentralized Fault Detection and Isolation Strategy for Networked Multirobot Systems
,” IEEE Trans. Control Systems Technol.
, 23
(4
), pp. 1465
–1476
. 10.1109/TCST.2014.237717511.
Januário
, F.
, Cardoso
, A.
, and Gil
, P.
, 2019
, “A Distributed Multi-Agent Framework for Resilience Enhancement in Cyber-Physical Systems
,” IEEE Access
, 7
, pp. 31342
–31357
. 10.1109/ACCESS.2019.290362912.
Amullen
, E. M.
, Shetty
, S.
, and Keel
, L. H.
, 2016
, “Model-based Resilient Control for a Multi-Agent System Against Denial of Service Attacks
,” Proceedings of 2016 World Automation Congress
, Rio Grande, Puerto Rico
, July 31–Aug. 4
, p. 1570244877
.13.
Cui
, L.
, Hu
, J.
, Park
, B. B.
, and Bujanovic
, P.
, 2018
, “Development of a Simulation Platform for Safety Impact Analysis Considering Vehicle Dynamics, Sensor Errors, and Communication Latencies: Assessing Cooperative Adaptive Cruise Control Under Cyber Attack
,” Transportation Research Part C: Emerging Technologies
, 97
, pp. 1
–22
. 10.1016/j.trc.2018.10.00514.
Petrillo
, A.
, Pescapé
, A.
, and Santini
, S.
, 2018
, “A Collaborative Approach for Improving the Security of Vehicular Scenarios: The Case of Platooning
,” Computer Communications
, 122
, pp. 59
–75
. 10.1016/j.comcom.2018.03.01415.
Iftekhar
, L.
, and Olfati-Saber
, R.
, 2012
, “Autonomous Driving for Vehicular Networks With Nonlinear Dynamics
,” Proceedings of Intell. Veh. Symposium
, Alcala de Henares, Spain
, June 3–7
, pp. 723
–729
.16.
Olfati-Saber
, R.
, 2006
, “Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory
,” IEEE Trans. Automatic Control
, 51
(3
), pp. 401
–420
. 10.1109/TAC.2005.86419017.
Wang
, F.
, and Chen
, Y.
, 2019
, “Energy-Efficient Flocking Control: A Distributed Least-Informed Method
,” Proceedings of the 2019 IEEE Conference on Control Technology and Applications
, Hong Kong, China
, Aug. 19–21
, pp. 332
–337
.18.
Wang
, F.
, and Chen
, Y.
, 2020
, “Fast Convergent Flocking Control of Multi-Agent Systems With Switching Communication Topology
,” Proceedings of the 2020 American Control Conference
, Denver, CO
, July 1–3
, pp. 695
–700
.19.
Wang
, F.
, and Chen
, Y.
, 2018
, “A Novel Autonomous Trajectory Control for Vehicular Cyber-Physical Systems With Flocking Control Algorithms
,” Proc. of the 2018 Amer. Control Conf.
, Milwaukee, MI
, June 25–27
, pp. 5076
–5081
.20.
Yu
, W.
, Chen
, G.
, and Cao
, M.
, 2010
, “Some Necessary and Sufficient Conditions for Second-Order Consensus in Multi-Agent Dynamical Systems
,” Automatica
, 46
(6
), pp. 1089
–1095
. 10.1016/j.automatica.2010.03.00621.
Olfati-Saber
, R.
, and Murray
, R. M.
, 2004
, “Consensus Problems in Networks of Agents with Switching Topology and Time-Delays
,” IEEE Trans. Autom. Control
, 49
(9
), pp. 1520
–1533
. 10.1109/TAC.2004.83411322.
Alessandretti
, A.
, Aguiar
, A. P.
, and Jones
, C. N.
, “Trajectory-Tracking and Path-Following Controllers for Constrained Underactuated Vehicles Using Model Predictive Control
,” Proc. of 2013 IEEE European Control Conf.
, Zurich, Switzerland
, July 2013
, pp. 1371
–1376
.23.
Indiveri
, G.
, “Kinematic Time-Invariant Control of a 2D Nonholonomic Vehicle
,” Proceedings of the 38th IEEE Conf. on Decision and Control
, Phoenix, AZ
, Dec. 1999
, pp. 2112
–2117
.24.
Misawa
, E. A.
, and Hedrick
, J. K.
, 1989
, “Nonlinear Observers—A State-of-the-Art Survey
,” ASME J. Dyn. Syst., Meas., Control
, 111
(3
), pp. 344
–352
. 10.1115/1.315305925.
Reif
, K.
, Gunther
, S.
, Yaz
, E.
, and Unbehauen
, R.
, 1999
, “Stochastic Stability of the Discrete-Time Extended Kalman Filter
,” IEEE Trans. Automatic Control
, 44
(4
), pp. 714
–728
. 10.1109/9.75480926.
Wenzel
, T. A.
, Burnham
, K. J.
, Blundell
, M. V.
, and Williams
, R. A.
, 2006
, “Dual Extended Kalman Filter for Vehicle State and Parameter Estimation
,” Veh. Syst. Dyn.
, 44
(2
), pp. 153
–171
. 10.1080/0042311050038594927.
Wang
, F.
, and Chen
, Y.
, 2020
, “A Novel Hierarchical Flocking Control Framework for Connected and Automated Vehicles
,” IEEE Trans. Intell. Transp. Syst.
, pp. 1
–12
. 10.1109/TITS.2020.2986436Copyright © 2021 by ASME
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