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Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach

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Abstract

The frequent traffic congestion on the highways has necessitated the formulation of a suitable traffic control strategy that reduces transportation time. The main objective of any highway traffic control strategy is to regulate the traffic flow in such a manner that the participating vehicles can travel as fast as possible without any congestion. To accommodate this goal and to maintain a steady stream of vehicles on the highway, this work proposes a Model Predictive based Sliding mode Cooperative and Integrated Control that produces a real-time applicable, optimal, robust, and stable control command. In this sense, the traffic control problem is reformulated as a second-order nonlinear affine state space model, and then, the resulting control signal is derived via Model Predictive based Sliding Model Control (MPSMC). The proposed method delivers better results w.r.t established strategies in terms of Total Time Spent (TTS) and computation time. Furthermore, the Utilization Cost Function has been introduced in this work, rather than TTS, and it has been applied to the optimization problem of MPSMC to better utilize the existing characteristics of the highway, which has yielded a smoother traffic flow.

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Abbreviations

MPSMC :

Model Predictive based Sliding Model Control

TTS :

Total Time Spent

HTCSs :

Highway Traffic Control Strategies

RM :

Ramp Metering

VSL :

Variable Speed Limit

LCC :

Lane Change Control

CTM :

Cell Transmission Model

SMC :

Sliding Mode Control

VMS :

Variable Message Signs

PMP :

Pontryagin Minimum Principal

TTT :

Total Travel Time

TWT :

Total Waiting Time

mAMOC :

Modified AMOC

References

  1. Tedjopurnomo, D.A., et al.: A survey on modern deep neural network for traffic prediction: Trends, methods and challenges. IEEE Trans. Knowl. Data Eng. 34(4), 1544–1561 (2020)

  2. Haydari, A., Yılmaz, Y.: Deep reinforcement learning for intelligent transportation systems: A survey. IEEE Trans. Intell. Transp. Syst. 23(1), 11–32 (2020)

  3. van de Weg, G.S., et al.: Efficient freeway MPC by parameterization of ALINEA and a speed-limited area. IEEE Transactions on Intelligent Transportation Systems 20(1), 16–29 (2018)

    Google Scholar 

  4. Guo, Q., Li, L., Xuegang, J.B.: Urban traffic signal control with connected and automated vehicles: A survey. Transportation research part C: emerging technologies 101, 313–334 (2019)

    Article  Google Scholar 

  5. Papamichail, I., et al.: Coordinated ramp metering for freeway networks–a model-predictive hierarchical control approach. Transportation Research Part C: Emerging Technologies 18(3), 311–331 (2010)

    Article  Google Scholar 

  6. Frejo, J.R.D., Camacho, E.F.: Global versus local MPC algorithms in freeway traffic control with ramp metering and variable speed limits. IEEE Transactions on intelligent transportation systems 13(4), 1556–1565 (2012)

    Article  Google Scholar 

  7. Kušić, K., et al.: An overview of reinforcement learning methods for variable speed limit control. Applied Sciences 10(14), 4917 (2020)

    Article  Google Scholar 

  8. Groot, N., De Schutter, B., Hellendoorn, H.: Integrated model predictive traffic and emission control using a piecewise-affine approach. IEEE Transactions on Intelligent Transportation Systems 14(2), 587–598 (2012)

    Article  Google Scholar 

  9. Frejo, J.R.D., De Schutter, B.: Logic-Based Traffic Flow Control for Ramp Metering and Variable Speed Limits—Part 1: Controller. IEEE Transactions on Intelligent Transportation Systems 22(5), 2647–2657 (2020)

    Article  Google Scholar 

  10. Chen, J., et al.: Adaptive ramp metering control for Urban freeway using large-scale data. IEEE Transactions on Vehicular Technology 68(10), 9507–9518 (2019)

    Article  Google Scholar 

  11. Papageorgiou, M., Hadj-Salem, H., Blosseville, J.-M.: ALINEA: A local feedback control law for on-ramp metering. Transp. Res. Rec. 1320(1), 58–67 (1991)

    Google Scholar 

  12. Frejo, J.R.D., De Schutter, B.: Feed-forward ALINEA: A ramp metering control algorithm for nearby and distant bottlenecks. IEEE Transactions on Intelligent Transportation Systems 20(7), 2448–2458 (2018)

    Article  Google Scholar 

  13. Iordanidou, G.-R., et al.: Feedback-based integrated motorway traffic flow control with delay balancing. IEEE Transactions on Intelligent Transportation Systems 18(9), 2319–2329 (2017)

    Article  Google Scholar 

  14. Goatin, P., Göttlich, S., Kolb, O.: Speed limit and ramp meter control for traffic flow networks. Eng. Optim. 48(7), 1121–1144 (2016)

    Article  MathSciNet  Google Scholar 

  15. Wang, Xu., Niu, L.: Integrated variable speed limit and ramp metering control study on flow interaction between mainline and ramps. Adv. Mech. Eng. 11(3), 1687814019831913 (2019)

    Article  Google Scholar 

  16. Zhang, Y., Ioannou, P.A.: Combined variable speed limit and lane change control for highway traffic. IEEE Trans. Intell. Transp. Syst. 18(7), 1812–1823 (2016)

    Article  Google Scholar 

  17. Zhang, Y., Ioannou, P.A.: Integrated control of highway traffic flow. Journal of Control and Decision 5(1), 19–41 (2018)

    Article  MathSciNet  Google Scholar 

  18. Zhang, Y., Ioannou, P.A.: Stability analysis and variable speed limit control of a traffic flow model. Transportation Research Part B: Methodological 118, 31–65 (2018)

    Article  Google Scholar 

  19. Aval, T., Soroush, S., Eghbal, N.: Feedback-based cooperative ramp metering for highway traffic flow control: A model predictive sliding mode control approach. Int. J. Robust Nonlinear Control 30(18), 8259–8277 (2020)

    Article  MathSciNet  Google Scholar 

  20. Messner, A., Papageorgiou, M.: METANET: A macroscopic simulation program for motorway networks. Traffic engineering & control 31(8–9), 466–470 (1990)

    Google Scholar 

  21. Kotsialos, A., et al.: Coordinated and integrated control of motorway networks via non-linear optimal control. Transportation Research Part C: Emerging Technologies 10(1), 65–84 (2002)

    Article  Google Scholar 

  22. Poole, A., Kotsialos, A.: METANET validation of the large-scale Manchester ring-road network using gradient-based and particle swarm optimization. IEEE Trans. Intell. Transp. Syst. 19(7), 2055–2065 (2017)

    Article  Google Scholar 

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Correspondence to Seyed Soroush Tabadkani Avval.

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Avval, S.S.T., Eghbal, N. Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach. Int. J. ITS Res. 22, 216–228 (2024). https://doi.org/10.1007/s13177-024-00391-7

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