http://iet.metastore.ingenta.com
1887

Cooperative adaptive cruise control in mixed traffic with selective use of vehicle-to-vehicle communication

Cooperative adaptive cruise control in mixed traffic with selective use of vehicle-to-vehicle communication

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Intelligent Transport Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study is focused on the design of cooperative adaptive cruise control (CACC) to regulate the longitudinal motion of connected and automated vehicles (CAVs) in mixed traffic that is composed of human-driven vehicles and CAVs. Wireless vehicle-to-vehicle communication is exploited to monitor the motion of multiple broadcasting vehicles, and a strategy is designed to determine whether the received data of other vehicles are incorporated into CACC. A condition is derived for choosing control gains that ensure the internal stability of CAVs in the presence of time delays and switching connectivity topologies of information flow. Moreover, because the switching connectivity topologies may change the dynamics of the whole vehicle chain, the authors apply a data-driven approach for online optimisation of control gains such that CACC adapts to the variations of connectivity topologies. The proposed selective CACC is validated through numerical simulations. To enhance the fidelity of simulations, they use the data collected through on-road experiments to simulate the motion of human-driven vehicles and apply the physics-based vehicle dynamic model to simulate the motion of CAVs. Simulation results demonstrate the advantages of the proposed selective CACC in improving vehicle safety and in mitigating perturbations in mixed traffic.

References

    1. 1)
      • 1. Vahidi, A., Eskandarian, A.: ‘Research advances in intelligent collision avoidance and adaptive cruise control’, IEEE Trans. Intell. Transp. Syst., 2003, 4, (3), pp. 143153.
    2. 2)
      • 2. Dar, K., Bakhouya, M., Gaber, J., et al: ‘Wireless communication technologies for ITS application’, IEEE Commun. Mag., 2010, 48, (5), pp. 156162.
    3. 3)
      • 3. Morgan, Y.L.: ‘Notes on DSRC & WAVE standards suite: its architecture, design, and characteristics’, IEEE Commun. Surv. Tutor., 2010, 12, (4), pp. 504518.
    4. 4)
      • 4. Dey, K.C., Yan, L., Wang, X., et al: ‘A review of communication, driver characteristics, and controls aspects of cooperative adaptive cruise control’, IEEE Trans. Intell. Transp. Syst., 2016, 17, (2), pp. 491509.
    5. 5)
      • 5. Seiler, P., Pand, A., Hedrick, K.: ‘Disturbance propagation in vehicle strings’, IEEE Trans. Autom. Control, 2004, 49, (10), pp. 18351842.
    6. 6)
      • 6. Zhao, Y., Minero, P., Gupta, V.: ‘On disturbance propagation in leader-follower systems with limited leader information’, Automatica, 2014, 50, pp. 591598.
    7. 7)
      • 7. Naus, G.J.L., Vugts, R.P.A., Ploeg, J., et al: ‘String-stable CACC design and experimental validation: a frequency-domain approach’, IEEE Trans. Veh. Technol., 2010, 59, (9), pp. 42684279.
    8. 8)
      • 8. Ploeg, J., Shukla, D.P., van de Wouw, N., et al: ‘Controller synthesis for string stability of vehicle platoons’, IEEE Trans. Intell. Transp. Syst., 2014, 15, (2), pp. 854865.
    9. 9)
      • 9. Zheng, Y., Li, S.E., Wang, J., et al: ‘Stability and scalability of homogeneous vehicular platoon: study on the influence of information flow topologies’, IEEE Trans. Intell. Transp. Syst., 2016, 17, (1), pp. 1426.
    10. 10)
      • 10. Milanés, V., Shladover, S.E.: ‘Modeling cooperative and autonomous adaptive cruise control dynamic response using experimental data’, Transp. Res. C, 2014, 48, pp. 285300.
    11. 11)
      • 11. Robinson, T., Chan, E., Coelingh, E.: ‘Operating platoons on public motorways: an introduction to the SARTRE platooning programme’. Proc. 17th World Congress on Intelligent Transport Systems, 2010, pp. 111.
    12. 12)
      • 12. Geiger, A., Lauer, M., Moosmann, F., et al: ‘Team AnnieWAY's entry to the 2011 grand cooperative driving challenge’, IEEE Trans. Intell. Transp. Syst., 2012, 13, (3), pp. 10081017.
    13. 13)
      • 13. Alam, A., Mårtensson, J., Johansson, K.H.: ‘Experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning’, Control Eng. Pract., 2015, 38, pp. 1125.
    14. 14)
      • 14. Zhang, L., Orosz, G.: ‘Motif-based design for connected vehicle systems in presence of heterogeneous connectivity structures and time delays’, IEEE Trans. Intell. Transp. Syst., 2016, 17, (6), pp. 16381651.
    15. 15)
      • 15. Zhang, L., Sun, J., Orosz, G.: ‘Hierarchical design of connected cruise control in the presence of information delays and uncertain vehicle dynamics’, IEEE Trans. Control Syst. Technol., 2018, 26, (1), pp. 139150.
    16. 16)
      • 16. Avedisov, S.S., Orosz, G.: ‘Nonlinear network modes in cyclic systems with applications to connected vehicles’, J. Nonlinear Sci., 2015, 25, (4), pp. 10151049.
    17. 17)
      • 17. Zhang, L., Orosz, G.: ‘Consensus and disturbance attenuation in multi-agent chains with nonlinear control and time delays’, Int. J. Robust Nonlinear Control, 2017, 27, (5), pp. 781803.
    18. 18)
      • 18. Qin, W.B., Gomez, M.M., Orosz, G.: ‘Stability and frequency response under stochastic communication delays with applications to connected cruise control design’, IEEE Trans. Intell. Transp. Syst., 2017, 18, (2), pp. 388403.
    19. 19)
      • 19. Ge, J.I., Orosz, G.: ‘Optimal control of connected vehicle systems with communication delay and driver reaction time’, IEEE Trans. Intell. Transp. Syst., 2017, 18, (8), pp. 20562070.
    20. 20)
      • 20. Marino, R., Scalzi, S., Netto, M.: ‘Nested PID steering control for lane keeping in autonomous vehicles’, Control Eng. Pract., 2011, 19, (12), pp. 14591467.
    21. 21)
      • 21. Kenney, J.B.: ‘Dedicated short-range communications (DSRC) standards in the United States’, Proc. IEEE, 2011, 99, pp. 11621182.
    22. 22)
      • 22. Bergenhem, C., Hedin, E., Skarin, D.: ‘Vehicle-to-vehicle communication for a platooning system’, Procedia – Soc. Behav. Sci., 2012, 48, pp. 12221233.
    23. 23)
      • 23. Zhang, L., Orosz, G.: ‘Black-box modeling of connected vehicle networks’. Proc. American Control Conf., 2016, pp. 24212426.
    24. 24)
      • 24. Lofberg, J.: ‘YALMIP: a toolbox for modeling and optimization in MATLAB’. IEEE Symp. on Computer Aided Control Systems Design, 2004, pp. 284289.
    25. 25)
      • 25. Bezzina, D., Sayer, J.: ‘Safety pilot model deployment: test conductor team report(Report No. DOT HS 812 171), 2015.
    26. 26)
      • 26. Orosz, G., Wilson, R.E., Stépán, G.: ‘Traffic jams: dynamics and control’, Philos. Trans. R. Soc. A, 2010, 368, (1928), pp. 44554479.
    27. 27)
      • 27. Kesting, A., Treiber, M., Helbing, D.: ‘Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity’, Philos. Trans. R. Soc. A, 2010, 368, (1928), pp. 45854605.
    28. 28)
      • 28. Zhang, L., Orosz, G.: ‘Beyond-line-of-sight identification by using vehicle-to-vehicle communication’, IEEE Trans. Intell. Transp. Syst., 2018, 19, (6), pp. 19621972.
    29. 29)
      • 29. Krstic, M.: ‘Delay compensation for nonlinear, adaptive and PDE systems’ (Birkhäuser, New York, USA, 2009).
    30. 30)
      • 30. Ulsoy, A.G., Peng, H., Çakmakci, M.: ‘Automotive control systems’ (Cambridge University Press, 2012).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2018.5235
Loading

Related content

content/journals/10.1049/iet-its.2018.5235
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address