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Multiclass first-order simulation model to explain non-linear traffic phenomena

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  • Ngoduy, D.
  • Liu, R.

Abstract

With the first-order traffic model of Lighthill, Whitham and Richard (LWR), many simple traffic problems can be represented analytically such as a shock formation. However, the LWR model has some deficiencies. For example, among the other things, it fails to replicate interesting non-linear phenomena such as hysteresis and capacity drop as well as the dispersion of traffic platoon when there exists a distribution of desired speeds in heterogeneous traffic. To this end, in this paper, we propose a novel multiclass first-order simulation model based on an approximation of Riemann solver. In the developed model, each vehicle class is only characterized by their desired speeds in a free-flow traffic state where overtaking is allowed. However, when traffic is congested, all vehicle classes must travel at the same congested speed and overtaking is not possible. Numerical results show that the proposed model is not only more accurate and reliable than the existing models but also able to explain non-linear traffic phenomena on freeways.

Suggested Citation

  • Ngoduy, D. & Liu, R., 2007. "Multiclass first-order simulation model to explain non-linear traffic phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 667-682.
  • Handle: RePEc:eee:phsmap:v:385:y:2007:i:2:p:667-682
    DOI: 10.1016/j.physa.2007.07.041
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    References listed on IDEAS

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    1. Cassidy, Michael J., 1998. "Bivariate relations in nearly stationary highway traffic," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 49-59, January.
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    3. Wong, G. C. K. & Wong, S. C., 2002. "A multi-class traffic flow model - an extension of LWR model with heterogeneous drivers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 827-841, November.
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    Cited by:

    1. Mohammadian, Saeed & Zheng, Zuduo & Haque, Mazharul & Bhaskar, Ashish, 2023. "NET-RAT: Non-equilibrium traffic model based on risk allostasis theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    2. Ngoduy, D., 2008. "Applicable filtering framework for online multiclass freeway network estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 599-616.
    3. Yan, Fei & Qiu, Jiangchen & Tian, Jianyan, 2022. "An iterative learning identification strategy for nonlinear macroscopic traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Xiang Wang & Po Zhao & Yanyun Tao, 2018. "Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model," Sustainability, MDPI, vol. 10(12), pages 1-22, December.
    5. Mohammadian, Saeed & Zheng, Zuduo & Haque, Md. Mazharul & Bhaskar, Ashish, 2021. "Performance of continuum models for realworld traffic flows: Comprehensive benchmarking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 132-167.
    6. Mohan, Ranju & Ramadurai, Gitakrishnan, 2021. "Multi-class traffic flow model based on three dimensional flow–concentration surface," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    7. Ngoduy, D. & Hoogendoorn, S.P. & Liu, R., 2009. "Continuum modeling of cooperative traffic flow dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(13), pages 2705-2716.
    8. (Sean) Qian, Zhen & Li, Jia & Li, Xiaopeng & Zhang, Michael & Wang, Haizhong, 2017. "Modeling heterogeneous traffic flow: A pragmatic approach," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 183-204.
    9. Yibing Wang & Long Wang & Xianghua Yu & Jingqiu Guo, 2023. "Capacity Drop at Freeway Ramp Merges with Its Replication in Macroscopic and Microscopic Traffic Simulations: A Tutorial Report," Sustainability, MDPI, vol. 15(3), pages 1-27, January.

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