access icon free Multi-agent model-based predictive control for large-scale urban traffic networks using a serial scheme

Urban traffic networks are large-scale systems, consisting of many intersections controlled by traffic lights and interacting connected links. For efficiently regulating the traffic flows and mitigating the traffic congestion in cities, a network-wide control strategy should be implemented. Control of large-scale traffic networks is often infeasible by only using a single controller, that is, in a centralised way, because of the high dimension, complicated dynamics and uncertainties of the system. In this study, the authors propose a multi-agent control approach using a congestion-degree-based serial scheme. Each agent employs a model-based predictive control approach and communicates with its neighbours. The congestion-degree-based serial scheme helps the agents to reach an agreement on their decisions regarding traffic control actions as soon as possible. A simulation study is carried out on a hypothetical large-scale urban traffic network based on the presented control strategy. The results illustrate that this approach has a better performance with regard to computation time compared with the centralised control method and a faster convergence speed compared with the classical parallel scheme.

Inspec keywords: multi-agent systems; computational complexity; road traffic control; predictive control; convergence; large-scale systems

Other keywords: congestion-degree-based serial scheme; hypothetical large-scale urban traffic network; convergence speed; traffic lights; centralised control method; traffic control actions; traffic congestion mitigation; traffic flows; multi-agent control approach; network-wide control strategy; computation time; model-based predictive control approach; parallel scheme

Subjects: Road-traffic system control; Optimal control; Computational complexity; Multivariable control systems

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
      • 2. Lowrie, P.R.: ‘The Sydney coordinated adaptive traffic system-principles, methodology, algorithms’. Proc. Int. Conf. on Road Traffic Signalling, London, United Kingdom, March 1982, pp. 6770.
    6. 6)
      • 22. Bertsekas, D.P., Tsitsiklis, J.N.: ‘Parallel and distributed computation: numerical methods’ (Prentice-Hall Press, 1989).
    7. 7)
    8. 8)
      • 27. Georges, D.: ‘Decentralized adaptive control for a water distribution system’. Proc. Third IEEE Conf. on Control Applications, Glasgow, UK, August 1994, pp. 14111416.
    9. 9)
    10. 10)
      • 1. Hunt, P.B., Robertson, D.I., Bretherton, R.D., et al: ‘The SCOOT on-line traffic signal optimisation technique’, Traffic Eng. Control, 1982, 23, (4), pp. 190192.
    11. 11)
    12. 12)
    13. 13)
      • 29. Geroliminis, N., Daganzo, C.F.: ‘Macroscopic modeling of traffic in cities’. Proc. Transp. Research Board 86th Annual Meeting, Washington DC, USA, January 2007, no. 07-0413.
    14. 14)
    15. 15)
    16. 16)
    17. 17)
      • 23. Boyd, S.P., Vandenberghe, L.: ‘Convex optimization’ (Cambridge University Press, 2004).
    18. 18)
      • 21. Bertsekas, D.P.: ‘Constrained optimization and lagrange multiplier methods’ (Academic Press, 1982).
    19. 19)
      • 6. Aboudolas, K., Papageorgiou, M., Kosmatopoulos, E.: ‘Control and optimization methods for traffic signal control in large-scale congested urban road networks’. Proc. American Control Conf., New York, USA, July 2007, pp. 31323138.
    20. 20)
    21. 21)
      • 26. Fawal, H.E., Georges, D., Bornard, G.: ‘Optimal control of complex irrigation systems via decomposition-coordination and the use of augmented Lagrangian’. Proc. IEEE Int. Conf. on Systems, Man, and Cybernetics, San Diego, USA, October 1998, pp. 38743879.
    22. 22)
      • 31. Zegeye, S., De Schutter, B., Hellendoorn, J., et al: ‘Parameterized MPC to reduce dispersion of road traffic emissions’. Proc. American Control Conf., San Francisco, USA, June 2011, pp. 44284433.
    23. 23)
    24. 24)
    25. 25)
      • 3. Gartner, N.H.: ‘OPAC: a demand-responsive strategy for traffic signal control’, Transp. Res. Record, 1983, 1983, (906), pp. 7581.
    26. 26)
    27. 27)
    28. 28)
    29. 29)
    30. 30)
    31. 31)
      • 32. Lin, S., Zhou, Z., Xi, Y.: ‘Analysis of Performance Criteria for Model-Based Traffic Congestion Control in Urban Road Networks’. Proc. Transportation Research Board 92nd Annual Meeting, Washington DC, USA, January 2013, no. 13-1775.
    32. 32)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2014.0490
Loading

Related content

content/journals/10.1049/iet-cta.2014.0490
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading