Technical Papers
Apr 28, 2020

Consensus Phenomenon and Characteristics of Vehicle Cooperative Driving

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 7

Abstract

The consensus degree among vehicles is an important index to measure the cooperative driving system. First, this paper establishes a measurement method of the instantaneous consensus of an individual vehicle to evaluate the consensus degree. On this basis, the consensus degree index of the cooperative driving system on the road section is constructed; thus, a quantitative description method for the consensus of vehicle cooperative driving is formed. The simulation experiment explores the consensus phenomenon and characteristics of the vehicle cooperative driving system by means of the classic vehicle cooperative driving model. The results show that the consensus index of the vehicle cooperative driving system proposed in this paper is effective and can better describe the consensus phenomenon in traffic.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The type of data is a piece of code about the consensus index proposed in this paper.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61573075), the National Key R&D Program, China (Grant No. 2016YFB0100904), and the Natural Science Foundation of Chongqing (Grant No. cstc2017jcyjBX0001).

References

Artuñedo, A., R. M. Del Toro, and R. E. Haber. 2017. “Consensus-based cooperative control based on pollution sensing and traffic information for urban traffic networks.” Sensors 7 (5): 1–16. https://doi.org/10.3390/s17050953.
di Bernardo, M., A. Salvi, and S. Santini. 2015. “Distributed consensus strategy for platooning of vehicles in the presence of time-varying heterogeneous communication delays.” IEEE Trans. Intell. Transp. Syst. 16 (1): 102–112. https://doi.org/10.1109/tits.2014.2328439.
Fax, J. A., and R. M. Murray. 2004. “Information flow and cooperative control of vehicle formations.” IEEE Trans. Autom. Control 49 (9): 1465–1476. https://doi.org/10.1109/TAC.2004.834433.
Gao, Y. L., J. Yu, J. Shao, and M. Yu. 2016. “Group consensus for second-order discrete-time multi-agent systems with time-varying delays under switching topologies.” Neurocomputing 207 (Sep): 805–812. https://doi.org/10.1016/j.neucom.2016.05.062.
He, W. L., G. R. Chen, Q. L. Han, and F. Qian. 2017. “Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control.” Inf. Sci. 380 (Feb): 145–158. https://doi.org/10.1016/j.ins.2015.06.005.
Kim, B. Y., and H. S. Ahn. 2016. “Distributed coordination and control for a freeway traffic network using consensus algorithms.” IEEE Syst. J. 10 (1): 162–168. https://doi.org/10.1109/JSYST.2014.2318054.
Li, X. W., C. S. Yeng, and L. H. Xie. 2018a. “Robust consensus of uncertain linear multi-agent systems via dynamic output feedback.” Automatica 98 (Dec): 114–123. https://doi.org/10.1016/j.automatica.2018.09.020.
Li, Y. F., C. C. Tang, S. Peeta, and Y. B. Wang. 2018b. “Nonlinear consensus-based connected vehicle platoon control incorporating car-following interactions and heterogeneous time delays.” IEEE Trans. Intell. Transp. Syst. 20 (6): 2209–2219. https://doi.org/10.1109/TITS.2018.2865546.
Li, Z. K., Z. S. Duan, G. R. Chen, and L. Huang. 2010. “Consensus of multiagent systems and synchronization of complex networks: A unified viewpoint.” IEEE Trans. Circuits Syst. I-Regul. Pap. 57 (1): 213–224. https://doi.org/10.1109/TCSI.2009.2023937.
Liu, H., D. H. Sun, and M. Zhao. 2015. “Analysis of traffic flow based on car-following theory: A cyber-physical perspective.” Nonlinear Dyn. 84 (2): 881–893. https://doi.org/10.1007/s11071-015-2534-y.
Liu, H., D. H. Sun, and M. Zhao. 2016. “A model prediction control based framework for optimization of signaled intersection: A cyber-physical perspective.” Optik 127 (20): 10068–10075. https://doi.org/10.1016/j.ijleo.2016.07.094.
Ma, C. Q., and J. F. Zhang. 2010. “Necessary and sufficient conditions for consensusability of linear multi-agent systems.” IEEE Trans. Autom. Control 55 (5): 1263–1268. https://doi.org/10.1109/TAC.2010.2042764.
Mo, L., Y. G. Niu, and T. T. Pan. 2015. “Consensus of heterogeneous multi-agent systems with switching jointly-connected interconnection.” Physica A 427 (41): 132–140. https://doi.org/10.1016/j.physa.2015.01.070.
Olfati, S. R., and R. M. Murray. 2004. “Consensus problems in networks of agents with switching topology and time-delays.” IEEE Trans. Autom. Control 49 (9): 1520–1533. https://doi.org/10.1109/TAC.2004.834113.
Park, M. J., O. M. Kwon, J. H. Park, S. M. Lee, and E. J. Cha. 2012. “Leader-following consensus criteria for multi-agent systems with time-varying delays and switching interconnection topologies.” Chin. Phys. B 21 (11): 110508. https://doi.org/10.1088/1674-1056/21/11/110508.
Petrillo, A., A. Salvi, S. Santini, and A. S. Valente. 2018. “Adaptive multi-agents synchronization for collaborative driving of autonomous vehicles with multiple communication delays.” Transp. Res. Part C-Emerging Technol. 86 (Jan): 372–392. https://doi.org/10.1016/j.trc.2017.11.009.
Punzo, V., M. T. Borzacchiello, and B. Ciuffo. 2011. “On the assessment of vehicle trajectory data accuracy and application to the Next Generation SIMulation (NGSIM) program data.” Transp. Res. Part. C-Emerging Technol. 19 (6): 1243–1262. https://doi.org/10.1016/j.trc.2010.12.007.
Qin, J., Q. Ma, Y. Shi, and L. Wang. 2017. “Recent advances in consensus of multi-agent systems: A brief survey.” IEEE Trans. Ind. Electron. 64 (6): 4972–4983. https://doi.org/10.1109/TIE.2016.2636810.
Ren, W., R. W. Beard, and E. M. Atkins. 2005. “A survey of consensus problems in multi-agent coordination.” In Proc., American Control Conf., 1859–1864. New York: IEEE. https://doi.org/10.1109/ACC.2005.1470239.
Ren, W., R. W. Beard, and E. M. Atkins. 2007. “Information consensus in multivehicle cooperative control.” IEEE Control Syst. Mag. 27 (2): 71–82. https://doi.org/10.1109/MCS.2007.338264.
Santini, S., A. Salvi, A. S. Valente, M. Segata, and R. L. Cigno. 2016. “A consensus-based approach for platooning with inter-vehicular communications and its validation in realistic scenarios.” IEEE Trans. Veh. Technol. 66 (3): 1–14. https://doi.org/10.1109/TVT.2016.2585018.
Seiler, P., A. Pant, and K. Hedrick. 2004. “Disturbance propagation in vehicle strings.” IEEE Trans. Autom. Control 49 (10): 1835–1841. https://doi.org/10.1109/TAC.2004.835586.
Su, Y., and J. Huang. 2012. “Two consensus problems for discrete-time multi-agent systems with switching network topology.” Automatica 48 (9): 1988–1997. https://doi.org/10.1016/j.automatica.2012.03.029.
Sun, Y. G., and L. Wang. 2012. “Consensus of second-order multi-agent systems with asymmetric delays.” Syst. Control Lett. 61 (8): 857–862. https://doi.org/10.1016/j.sysconle.2012.05.007.
Trentelman, H. L., T. Kiyotsugu, and M. Nima. 2013. “Robust synchronization of uncertain linear multi-agent systems.” IEEE Trans. Autom. Control 58 (6): 1511–1523. https://doi.org/10.1109/TAC.2013.2239011.
Wang, B., P. Shi, J. Wang, and Y. D. Song. 2012. “Novel LMI-based stability and stabilization analysis on impulsive switched system with time delays.” J. Franklin Inst. 349 (8): 2650–2663. https://doi.org/10.1016/j.jfranklin.2012.06.005.
Wen, G., G. Hu, Z. Zuo, Y. Zhao, and J. Cao. 2017. “Robustcontainment of uncertain linear multi-agent systems under adaptive protocols.” Int. J. Robust Nonlinear Control 27 (12): 2053–2069. https://doi.org/10.1002/rnc.3670.
Wen, G., Y. Yu, Z. Peng, and R. Ahmed. 2016. “Consensus tracking for second-order nonlinear multi-agent systems with switching topologies and a time-varying reference state.” Int. J. Control 89 (10): 2096–2106. https://doi.org/10.1080/00207179.2016.1149221.
Wu, Z. G., Y. Xu, Y. J. Pan, H. Su, and Y. Tang. 2018. “Event-triggered control for consensus problem in multi-agent systems with quantized relative state measurements and external disturbance.” IEEE Trans. Circuits Syst. I Regul. Pap. 65 (7): 2232–2242. https://doi.org/10.1109/TCSI.2017.2777504.
Xiao, F., and L. Wang. 2006. “State consensus for multi-agent systems with switching topologies and time-varying delays.” Int. J. Control 79 (10): 1277–1284. https://doi.org/10.1080/00207170600825097.
Xie, D. F., X. M. Zhao, and Z. B. He. 2018. “Heterogeneous traffic mixing regular and connected vehicles: Modeling and stabilization.” IEEE Intell. Transp. Syst. 20 (6): 2060–2071. https://doi.org/10.1109/TITS.2018.2857465.
Zheng, Y. S., J. Y. Ma, and L. Wang. 2018. “Consensus of hybrid multi-agent systems.” IEEE Trans. Neural Networks Learn. Syst. 29 (4): 1359–1365. https://doi.org/10.1109/TNNLS.2017.2651402.
Zuo, Z., and L. Tie. 2016. “Distributed robust finite-time non-linear consensus protocols for multi-agent systems.” Int. J. Syst. Sci. 47 (6): 1366–1375. https://doi.org/10.1080/00207721.2014.925608.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 146Issue 7July 2020

History

Received: Apr 22, 2019
Accepted: Jan 2, 2020
Published online: Apr 28, 2020
Published in print: Jul 1, 2020
Discussion open until: Sep 28, 2020

Permissions

Request permissions for this article.

Authors

Affiliations

Professor, Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing Univ., Chongqing 400044, China; Professor, College of Automation, Chongqing Univ., Chongqing 400044, China; mailing address: No. 174, Shazheng St., Shapingba District, Chongqing 400044, China. Email: [email protected]
Ph.D. Candidate, Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing Univ., Chongqing 400044, China; Ph.D. Candidate, College of Automation, Chongqing Univ., Chongqing 400044, China; mailing address: No. 174, Shazheng St., Shapingba District, Chongqing 400044, China (corresponding author). Email: [email protected]
Assistant Professor, College of Mechanical and Electrical Engineering, Chongqing Univ. of Arts and Sciences, Chongqing 402160, China; Assistant Professor, mailing address: No. 319, Honghe Ave., Yongchuan District, Chongqing 402160, China. Email: [email protected]
Assistant Professor, Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing Univ., Chongqing 400044, China; Assistant Professor, College of Automation, Chongqing Univ., Chongqing 400044, China; mailing address: No. 174, Shazheng St., Shapingba District, Chongqing 400044, China. Email: [email protected]
Zhong-Cheng Liu [email protected]
Ph.D. Candidate, Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing Univ., Chongqing 400044, China; Ph.D. Candidate, College of Automation, Chongqing Univ., Chongqing 400044, China; mailing address: No. 174, Shazheng St., Shapingba District, Chongqing 400044, China. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share