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Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway

Author

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  • Changyin Dong

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    School of Transportation, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China)

  • Hao Wang

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    School of Transportation, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China)

  • Quan Chen

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China
    School of Transportation, Southeast University, No. 2, Sipailou Road, Nanjing 211189, China)

  • Daiheng Ni

    (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, No. 130, Natural Resources Road, Amherst, MA 01003, USA)

  • Ye Li

    (School of Traffic and Transportation Engineering, Central South University, No. 932, South Lushan Road, Changsha 410075, China)

Abstract

To support the rapid growth of demand in passengers and freight, separating trucks and passenger-cars is a potential solution to improve traffic efficiency and safety. The primary purpose of this paper is to comprehensively assess the multilane separate freeway at Huludao Toll Station in Liaoning Province, China. Based on the configuration and segmentation of the freeway near a toll station, a six-step guidance strategy is designed to adapt to the separate organization mode. Five conventional traffic scenarios are designed in the Vissim platform for comparative analysis between different guidance strategies. To investigate the vehicle-to-infrastructure (V2I) environment, a microscopic testbed is established with cooperative car-following and lane-changing models using the MATLAB platform. The numerical simulation results show that the guidance strategy significantly improves efficiency and safety, and also reduces emissions and fuel consumption. Meanwhile, pre-guidance before toll channels outperforms the scenario only applied with guidance measures after toll plaza. Compared to conventional conditions, the assessment of pollutant emissions and fuel consumption also embodies the superiority of the other five scenarios, especially in the sections of toll plaza and channels with the lowest efficiency and safety level. Generally, all indexes indicate that the cooperative V2I technology is the best alternative for multilane separate freeways.

Suggested Citation

  • Changyin Dong & Hao Wang & Quan Chen & Daiheng Ni & Ye Li, 2019. "Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway," Sustainability, MDPI, vol. 11(11), pages 1-22, May.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3057-:d:235632
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    References listed on IDEAS

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    1. Tu, Huizhao & Li, Hao & van Lint, Hans & van Zuylen, Henk, 2012. "Modeling travel time reliability of freeways using risk assessment techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1528-1540.
    2. Chen Chen & Xiaohua Zhao & Hao Liu & Guichao Ren & Yunlong Zhang & Xiaoming Liu, 2019. "Assessing the Influence of Adverse Weather on Traffic Flow Characteristics Using a Driving Simulator and VISSIM," Sustainability, MDPI, vol. 11(3), pages 1-16, February.
    3. 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.
    4. Ivan Mareev & Dirk Uwe Sauer, 2018. "Energy Consumption and Life Cycle Costs of Overhead Catenary Heavy-Duty Trucks for Long-Haul Transportation," Energies, MDPI, vol. 11(12), pages 1-18, December.
    5. Edgar Talavera & Alberto Díaz-Álvarez & Felipe Jiménez & José E. Naranjo, 2018. "Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation," Energies, MDPI, vol. 11(1), pages 1-17, January.
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    1. Khalifa Mohammed Al-Sobai & Shaligram Pokharel & Galal M. Abdella, 2020. "Perspectives on the Capabilities for the Selection of Strategic Projects," Sustainability, MDPI, vol. 12(19), pages 1-20, October.

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