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A Back-of-Queue Model of a Signal-Controlled Intersection Approach Developed Based on Analysis of Vehicle Driver Behavior

Author

Listed:
  • Elżbieta Macioszek

    (Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland)

  • Damian Iwanowicz

    (Department of Road and Transport Engineering, Faculty of Civil and Environmental Engineering and Architecture, UTP University of Science and Technology in Bydgoszcz, Prof. S. Kaliskiego 7 Street, 85-796 Bydgoszcz, Poland)

Abstract

In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the number of passengers and vehicles on the road and the capacity limitations of transport networks, it has become necessary to use new technologies for intelligent control and traffic management. Intelligent transport systems use advanced technologies in the field of data gathering, information processing, and traffic control to meet current transport needs. To be able to effectively control and manage road traffic, it is necessary to have reliable mathematical models that allow for a faithful representation of the real traffic conditions. Models of this type are usually the basis of complex algorithms used in practice in road traffic control. The application of appropriate models reflecting the behavior of road users contributes to the reduction of congestion, the vehicles travel time on the transport network, fuel consumption and the emissions, which in turn support broadly understood energy savings. The article proposes a model that allows for the estimation of the maximum queue size at the signal-controlled intersection approach (so-called: maximum back-of-queue). This model takes into account the most important traffic characteristics of the vehicles forming this queue. The verification allowed for the conclusion that the proposed model is characterized by high compliance with the actual traffic and road conditions at the intersections with signal controllers located in built-up areas in Poland. The obtained compliance confirms the possibility of using the model for practical applications in calculating the maximum back-of-queue at signal-controlled intersections located in built-up areas in Poland.

Suggested Citation

  • Elżbieta Macioszek & Damian Iwanowicz, 2021. "A Back-of-Queue Model of a Signal-Controlled Intersection Approach Developed Based on Analysis of Vehicle Driver Behavior," Energies, MDPI, vol. 14(4), pages 1-25, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1204-:d:504359
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    References listed on IDEAS

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    1. Viti, Francesco & van Zuylen, Henk J., 2010. "Probabilistic models for queues at fixed control signals," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 120-135, January.
    2. Hao, Peng & Ban, Xuegang, 2015. "Long queue estimation for signalized intersections using mobile data," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 54-73.
    3. Srivastava, Anupam & Jin, Wen-Long & Lebacque, Jean-Patrick, 2015. "A modified Cell Transmission Model with realistic queue discharge features at signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 302-315.
    4. Elżbieta Macioszek, 2020. "Roundabout Entry Capacity Calculation—A Case Study Based on Roundabouts in Tokyo, Japan, and Tokyo Surroundings," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
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    Cited by:

    1. Elżbieta Macioszek & Anna Granà & Paulo Fernandes & Margarida C. Coelho, 2022. "New Perspectives and Challenges in Traffic and Transportation Engineering Supporting Energy Saving in Smart Cities—A Multidisciplinary Approach to a Global Problem," Energies, MDPI, vol. 15(12), pages 1-8, June.
    2. Yulong Pei & Xiaoxi Cai & Jie Li & Keke Song & Rui Liu, 2021. "Method for Identifying the Traffic Congestion Situation of the Main Road in Cold-Climate Cities Based on the Clustering Analysis Algorithm," Sustainability, MDPI, vol. 13(17), pages 1-31, August.
    3. Suhaib Alshayeb & Aleksandar Stevanovic & Nikola Mitrovic & Elio Espino, 2022. "Traffic Signal Optimization to Improve Sustainability: A Literature Review," Energies, MDPI, vol. 15(22), pages 1-24, November.
    4. Elżbieta Macioszek & Maria Cieśla & Anna Granà, 2023. "Future Development of an Energy-Efficient Electric Scooter Sharing System Based on a Stakeholder Analysis Method," Energies, MDPI, vol. 16(1), pages 1-24, January.
    5. Alicja Sołowczuk, 2021. "Effect of Traffic Calming in a Downtown District of Szczecin, Poland," Energies, MDPI, vol. 14(18), pages 1-21, September.

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