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A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data

Author

Listed:
  • Vittorio Astarita

    (Department of Civil Engineering, Università della Calabria, Via P. Bucci Cubo 46b, 87036 Rende (CS), Italy)

  • Vincenzo Pasquale Giofrè

    (Department of Civil Engineering, Università della Calabria, Via P. Bucci Cubo 46b, 87036 Rende (CS), Italy)

  • Giuseppe Guido

    (Department of Civil Engineering, Università della Calabria, Via P. Bucci Cubo 46b, 87036 Rende (CS), Italy)

  • Alessandro Vitale

    (Department of Civil Engineering, Università della Calabria, Via P. Bucci Cubo 46b, 87036 Rende (CS), Italy)

Abstract

New technologies such as “connected” and “autonomous” vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate traffic signal systems, in real time, has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not “connected” vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate traffic signal systems in real-time in a single intersection and in terms of cooperative-competitive paradigm between “connected” vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that “invisible vehicles” for the system (which are not “connected”) in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of a single intersection signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

Suggested Citation

  • Vittorio Astarita & Vincenzo Pasquale Giofrè & Giuseppe Guido & Alessandro Vitale, 2019. "A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data," Energies, MDPI, vol. 12(3), pages 1-22, January.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:409-:d:201403
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    References listed on IDEAS

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    1. Astarita, Vittorio & Bertini, Robert L. & d'Elia, Sergio & Guido, Giuseppe, 2006. "Motorway traffic parameter estimation from mobile phone counts," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1435-1446, December.
    2. Astarita, Vittorio & Guido, Giuseppe & Vitale, Alessandro & Giofré, Vincenzo, 2012. "A new microsimulation model for the evaluation of traffic safety performances," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 51, pages 1-2.
    3. Martin Cassini, 2010. "Traffic Lights: Weapons Of Mass Distraction, Danger And Delay," Economic Affairs, Wiley Blackwell, vol. 30(2), pages 79-80, June.
    4. E. Bavarez & G. F. Newell, 1967. "Traffic Signal Synchronization on a One-Way Street," Transportation Science, INFORMS, vol. 1(2), pages 55-73, May.
    5. John A. Hillier & Richard Rothery, 1967. "The Synchronization of Traffic Signals for Minimum Delay," Transportation Science, INFORMS, vol. 1(2), pages 81-94, May.
    6. Martin Cassini, 2006. "In Your Car No One Can Hear You Scream! Are Traffic Controls In Cities A Necessary Evil?," Economic Affairs, Wiley Blackwell, vol. 26(4), pages 75-78, December.
    7. Thorsten Neumann, 2010. "A Cost-Effective Method for the Detection of Queue Lengths at Traffic Lights," International Series in Operations Research & Management Science, in: Jaume Barceló & Masao Kuwahara (ed.), Traffic Data Collection and its Standardization, chapter 0, pages 151-160, Springer.
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    Cited by:

    1. Xu, Nan & Kong, Yan & Yan, Jinyue & Zhang, Yuanjian & Sui, Yan & Ju, Hao & Liu, Heng & Xu, Zhe, 2022. "Global optimization energy management for multi-energy source vehicles based on “Information layer - Physical layer - Energy layer - Dynamic programming” (IPE-DP)," Applied Energy, Elsevier, vol. 312(C).
    2. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    3. Sun, Bin & Zhang, Qijun & Wei, Ning & Jia, Zhenyu & Li, Chunming & Mao, Hongjun, 2022. "The energy flow of moving vehicles for different traffic states in the intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

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