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Energy dissipation of traffic flow at an on-ramp

Author

Listed:
  • Xue, Yu
  • Kang, San-Jun
  • Lu, Wei-Zhen
  • He, Hong-Di

Abstract

This paper proposes a new cellular automaton traffic model to study the energy dissipation in an on-ramp traffic system. Different from previous works, we investigate not only the traffic behavior in on-ramp flow system, but also the variation of energy dissipation in it. The numerical simulations are carried out and the influences of the injected probabilities and removed probability on energy dissipation are studied respectively. The results show there exist a critical point for the injected probability and a platform for energy dissipation. The results also indicate that the removed probability plays a chief role in avoiding traffic jam and reducing the energy dissipation, which is significant to explore the evolution of traffic congestion and the reduction of vehicle emission.

Suggested Citation

  • Xue, Yu & Kang, San-Jun & Lu, Wei-Zhen & He, Hong-Di, 2014. "Energy dissipation of traffic flow at an on-ramp," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 172-178.
    • Handle: RePEc:eee:phsmap:v:398:y:2014:i:c:p:172-178
    DOI: 10.1016/j.physa.2013.12.032
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    Citations

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    Cited by:

    1. Petinrin, J.O. & Shaaban, Mohamed, 2015. "Renewable energy for continuous energy sustainability in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 967-981.
    2. Xue Wang & Yu Xue & Suwei Feng, 2023. "Traffic fuel consumption evaluation of the on-ramp with acceleration lane based on cellular automata," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-11, June.
    3. Connor, Linda H., 2016. "Energy futures, state planning policies and coal mine contests in rural New South Wales," Energy Policy, Elsevier, vol. 99(C), pages 233-241.
    4. Jin, Zhizhan & Li, Zhipeng & Cheng, Rongjun & Ge, Hongxia, 2018. "Nonlinear analysis for an improved car-following model account for the optimal velocity changes with memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 278-288.
    5. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    6. Orlov, Anton, 2017. "Distributional effects of higher natural gas prices in Russia," Energy Policy, Elsevier, vol. 109(C), pages 590-600.
    7. Bonges, Henry A. & Lusk, Anne C., 2016. "Addressing electric vehicle (EV) sales and range anxiety through parking layout, policy and regulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 63-73.
    8. Qin, Shunda & He, Zhiting & Cheng, Rongjun, 2018. "An extended lattice hydrodynamic model based on control theory considering the memory effect of flux difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 809-816.
    9. Jin, Zhizhan & Yang, Zaili & Ge, Hongxia, 2018. "Energy consumption investigation for a new car-following model considering driver’s memory and average speed of the vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1038-1049.

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