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Research on Vehicle Congestion Group Identification for Evaluation of Traffic Flow Parameters

Author

Listed:
  • Marek Drliciak

    (Department of Highway and Environmental Engineering, Faculty of Civil Engineering, University of Žilina (UNIZA), Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Michal Cingel

    (University Science Park, University of Žilina (UNIZA), Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Jan Celko

    (Department of Highway and Environmental Engineering, Faculty of Civil Engineering, University of Žilina (UNIZA), Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Zuzana Panikova

    (Department of Highway and Environmental Engineering, Faculty of Civil Engineering, University of Žilina (UNIZA), Univerzitná 8215/1, 010 26 Žilina, Slovakia)

Abstract

The traffic flow parameters of the road network are most often evaluated through volumes, which are compared with its maximum volume (capacity) or speed and density. Capacity assessment was performed, considering horizontal and vertical orientation and characteristics of the traffic stream. This article presents the results of research on the identification of different states of creating congestion groups and their relationship to road capacity or decrease in speed. The following hypothesis was verified: when the capacity of the road is exceeded or almost reached, there is “always” a significant drop in the flow of traffic compared to when the capacity is not exceeded. The analysis showed that the average travel speed drops by 30% for the condition where groups of 25 or more vehicles are formed with a time interval of up to 4 s. The results make it possible to set traffic models in short time intervals according to real spatial conditions and to use them in the analysis of the environmental and safety impacts of road transport.

Suggested Citation

  • Marek Drliciak & Michal Cingel & Jan Celko & Zuzana Panikova, 2024. "Research on Vehicle Congestion Group Identification for Evaluation of Traffic Flow Parameters," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:1861-:d:1344957
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    References listed on IDEAS

    as
    1. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    2. Xuan Fang & Tamás Péter & Tamás Tettamanti, 2023. "Variable Speed Limit Control for the Motorway–Urban Merging Bottlenecks Using Multi-Agent Reinforcement Learning," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
    3. Lei Gong & Tianxu Wang & Tian Lei & Qin Luo & Zhu Han & Yihong Mo, 2023. "Daily Travel Mode Choice Considering Carbon Credit Incentive (CCI)—An Application of the Integrated Choice and Latent Variable (ICLV) Model," Sustainability, MDPI, vol. 15(20), pages 1-16, October.
    4. Lily Elefteriadou, 2014. "An Introduction to Traffic Flow Theory," Springer Optimization and Its Applications, Springer, edition 127, number 978-1-4614-8435-6, September.
    Full references (including those not matched with items on IDEAS)

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