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The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control

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  • Zhong, Zijia
  • Lee, Joyoung

Abstract

Traffic simulation is a cost-effective way to test the deployment of Cooperative Adaptive Cruise Control (CACC) vehicles in a large-scale transportation network. By using a previously developed microscopic simulation testbed, this paper examines the impacts of four managed lane strategies for the near-term deployment of CACC vehicles under mixed traffic conditions. Network-wide performance measures are investigated from the perspectives of mobility, safety, equity, and environmental impacts. In addition, the platoon formation performance of CACC vehicles is evaluated with platoon-orientated measures, such as the percentage of platooned CACC vehicles, average platoon depth, and vehicle-hour-platooned that is proposed in this paper under the imperfect DSRC communication environment. Moreover, managed lane score matrices are developed to incorporate heterogeneous categories of performance measures, aiming to provide a more comprehensive picture for stakeholders. The results show that mixing CACC traffic along with non-CACC traffic across all travel lanes is an acceptable option when the market penetration (MP) is lower than 30% for roadways where a managed lane is absent. Providing CACC with priority access to an existing managed lane, if available, is also a good strategy for improving the overall traffic performance when the MP is lower than 40%. When the MP reaches above 40%, a dedicated lane for CACC vehicles is recommended, as it provides greater opportunity for CACC vehicles to form platoons. The facilitation of homogeneous CACC traffic flow could make further improvements possible in the future.

Suggested Citation

  • Zhong, Zijia & Lee, Joyoung, 2019. "The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 257-270.
  • Handle: RePEc:eee:transa:v:129:y:2019:i:c:p:257-270
    DOI: 10.1016/j.tra.2019.08.015
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    References listed on IDEAS

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    1. Shewmake, Sharon & Jarvis, Lovell, 2014. "Hybrid cars and HOV lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 304-319.
    2. Georges M. Arnaout & Jean-Paul Arnaout, 2014. "Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(2), pages 186-199, March.
    3. Varaiya, Pravin, 2001. "Freeway Performance Measurement System, PeMS v3, Phase 1: Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt20p1j2w7, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Chengju Song & Hongfei Jia, 2022. "Multi-State Car-Following Behavior Simulation in a Mixed Traffic Flow for ICVs and MDVs," Sustainability, MDPI, vol. 14(20), pages 1-12, October.
    2. Zhang, Peng & Zhu, Huibing & Zhou, Yijiang, 2022. "Modeling cooperative driving strategies of automated vehicles considering trucks’ behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    3. Chen, Shuiwang & Hu, Lu & Yao, Zhihong & Zhu, Juanxiu & Zhao, Bin & Jiang, Yangsheng, 2022. "Efficient and environmentally friendly operation of intermittent dedicated lanes for connected autonomous vehicles in mixed traffic environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).

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