Abstract
Platoon formation of highway vehicles is a critical foundation for autonomous or semiautonomous vehicle control for enhanced safety, improved highway utility, increased fuel economy, and reduced emission toward intelligent transportation systems. Platoon control encounters great challenges from vehicle control, communications, team coordination, and uncertainties. This paper introduces a new method for coordinated control of platoons by using integrated network consensus decisions and vehicle control. To achieve suitable coordination of the team vehicles based on terrain and environmental conditions, the emerging technology of network consensus control is modified to a weighted and constrained consensus-seeking framework. Algorithms are introduced and their convergence properties are established. The methodology employs neighborhood information through on-board sensors and V2V or V2I communications, but achieves global coordination of the entire platoon. The ability of the methods in terms of robustness, disturbance rejection, noise attenuation, and cyber-physical interaction is analyzed and demonstrated with simulated case studies.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Hedrick J K, McMahon D, and Swaroop D, Vehicle modeling and control for automated highway systems, PATH Research Report, UCB-ITS-PRR-93-24, 1993.
Rajamani R, Tan H S, Law B, and Zhang W B, Demonstration of integrated lateral and longitudinal control for the operation of automated vehicles in platoons, IEEE Transactions on Control Systems Technology, 2000, 8(4): 695–708.
Choi S B and Hedrick J K, Vehicle longitudinal control using an adaptive observer for automated highway systems, Proc. of ACC, Seattle, 1995.
Liang C Y and Peng H E, String stability analysis of adaptive cruise controlled vehicles, JSME International Journal Series C, 2000, 43(3): 671–677.
Swaroop D and Hedrick J, String stability of interconnected systems, IEEE Transactions on Automatic Control, 1996, 41(3): 349–357.
Cortes J and Bullo F, Coordination and geometric optimization via distributed dynamical systems, SIAM J. Control Optim., 2005, 5: 1543–1574.
Huang M and Manton J H, Coordination and consensus of networked agents with noisy measurements: Stochastic algorithms and asymptotic behavior, SIAM J. Control Optim., 2009, 48(1): 134–161.
Huang M, Dey S, Nair G N, and Manton J H, Stochastic consensus over noisy networks with Markovian and arbitrary switches, Automatica, 2010, 46: 1571–1583.
Jadbabaie A, Lin J, and Morse A S, Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Trans. Automat. Contr., 2003, 48: 988–1000.
Ren W and Beard R W, Consensus seeking in multiagent systems under dynamically changing interaction topologies, IEEE Trans. Automat. Control, 2005, 50(5): 655–661.
Li T and Zhang J F, Consensus conditions of multi-agent systems with time-varying topologies and stochastic communication noises, IEEE Trans. on Automatic Control, 2010, 55(9): 2043–2057.
Li T, Fu M Y, Xie L H, and Zhang J F, Distributed consensus with limited communication data rate, IEEE Trans. on Automatic Control, 2011, 56(2): 279–292.
Yin G, Sun Y, and Wang L Y, Asymptotic properties of consensus-type algorithms for networked systems with regime-switching topologies, Automatica, 2011, 47: 1366–1378.
Yin G, Wang L Y, and Sun Y, Stochastic recursive algorithms for networked systems with delay and random switching: Multiscale formulations and asymptotic properties, Multiscale Modeling & Simulation, 2011, 9(3): 1087–1112.
Polyak B T, New method of stochastic approximation type, Automation Remote Control, 1991, 7: 937–946.
Ruppert D, Stochastic approximation, in Handbook in Sequential Analysis, eds. by Ghosh B K and Sen P K, Marcel Dekker, New York, 1991, 503–529.
Kushner H J and Yin G, Stochastic Approximation Algorithms and Applications, 2nd ed., Springer-Verlag, New York, 2003.
Nelson M B and Khasminskii R Z, Stochastic Approximation and Recursive Estimation, Amer. Math. Soc., Providence, RI, 1976.
Wang L Y and Yin G, Weighted and constrained consensus control with performance for robust distributed UAV deployments with dynamic information networks, Recent advances in UAV control systems, 2012.
Wang L Y, Wang C S, and Yin G, Weighted and constrained consensus for distributed power flow control, PMAPS 2012, Istanbul, Turkey, June 10–14, 2012.
Karlin S and Taylor H M, A First Course in Stochastic Processes, 2nd ed., Academic Press, New York, NY, 1975.
Horn R A and Johnson C R, Matrix Analysis, Cambridge University Press, 1985.
Kuo B C and Golnaraghi F, Automatic Control Systems, 8th ed., John Wiley & Sons, 2002.
Moreau L, Stability of multiagent systems with time-dependent communication links, IEEE Trans. Autom. Control, 2005, 50(2): 169–182.
Author information
Authors and Affiliations
Corresponding author
Additional information
The research was supported by the USA National Science Foundation under Grant No. CNS-1136007.
This paper was recommended for publication by Editor HONG Yiguang.
Rights and permissions
About this article
Cite this article
Wang, L.Y., Syed, A., Yin, G.G. et al. Control of vehicle platoons for highway safety and efficient utility: Consensus with communications and vehicle dynamics. J Syst Sci Complex 27, 605–631 (2014). https://doi.org/10.1007/s11424-014-2115-z
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-014-2115-z