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Approach to the Proecological Distribution of the Traffic Flow on the Transport Network from the Point of View of Carbon Dioxide

Author

Listed:
  • Piotr Gołębiowski

    (Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland)

  • Jolanta Żak

    (Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland)

  • Ilona Jacyna-Gołda

    (Faculty of Production Engineering, Warsaw University of Technology, 00-662 Warsaw, Poland)

Abstract

Nowadays, apart from travel time and cost, more and more attention is paid to ensuring that ecological footprint of the means of transport used for a journey is as small as possible. Therefore, it is reasonable to look for methods and solutions that will allow planning communication connections according to the principles of sustainable development. The aim of the article was to present mathematical model of the proecological distribution of traffic flow into a network, together with a determination of how the amount of emissions of harmful compounds for rail transport will be calculated (based on amount of energy necessary for movement, calculated on circumference of the wheels). The model has been verified on real data. The traffic flow was distributed over a selected communication route: Warszawa—Gdansk, where the criterion was minimization of total carbon dioxide emissions. An evolutionary method implemented in Microsoft Excel was used to solve the optimization problem. For the analysis of only the fastest connections, the railway one was the optimal from the point of view of the adopted criteria. After the train capacity was exceeded, air and car connections were loaded. Based on the research, a function that represents the amount of carbon dioxide emissions in the analyzed traffic route depending on the size of the traffic flow was developed.

Suggested Citation

  • Piotr Gołębiowski & Jolanta Żak & Ilona Jacyna-Gołda, 2020. "Approach to the Proecological Distribution of the Traffic Flow on the Transport Network from the Point of View of Carbon Dioxide," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6936-:d:404345
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    References listed on IDEAS

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    1. Denos C. Gazis & Robert Herman & Richard W. Rothery, 1961. "Nonlinear Follow-the-Leader Models of Traffic Flow," Operations Research, INFORMS, vol. 9(4), pages 545-567, August.
    2. Harold Greenberg, 1959. "An Analysis of Traffic Flow," Operations Research, INFORMS, vol. 7(1), pages 79-85, February.
    3. Kai Nagel & Peter Wagner & Richard Woesler, 2003. "Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling," Operations Research, INFORMS, vol. 51(5), pages 681-710, October.
    4. Martin Fellendorf & Peter Vortisch, 2010. "Microscopic Traffic Flow Simulator VISSIM," International Series in Operations Research & Management Science, in: Jaume Barceló (ed.), Fundamentals of Traffic Simulation, chapter 0, pages 63-93, Springer.
    5. Løvås, Gunnar G., 1994. "Modeling and simulation of pedestrian traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 28(6), pages 429-443, December.
    6. Denos C. Gazis & Robert Herman & Renfrey B. Potts, 1959. "Car-Following Theory of Steady-State Traffic Flow," Operations Research, INFORMS, vol. 7(4), pages 499-505, August.
    7. Zhang, H. M., 1998. "A theory of nonequilibrium traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 485-498, September.
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    Cited by:

    1. Piotr Gołębiowski & Marianna Jacyna & Andrzej Stańczak, 2021. "The Assessment of Energy Efficiency versus Planning of Rail Freight Traffic: A Case Study on the Example of Poland," Energies, MDPI, vol. 14(18), pages 1-18, September.
    2. Rafidah Md Noor & Nadia Bella Gustiani Rasyidi & Tarak Nandy & Raenu Kolandaisamy, 2020. "Campus Shuttle Bus Route Optimization Using Machine Learning Predictive Analysis: A Case Study," Sustainability, MDPI, vol. 13(1), pages 1-24, December.

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