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Cited by 88Traffic control and managementTransportation and Mobility InnovationsTransportation Planning and Optimization

Flow-level coordination of connected and autonomous vehicles in multilane freeway ramp merging areas

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Zhu, Jie, Tasic, Ivana, Qu, Xiaobo·2022·Multimodal Transportation
DOI 10.1016/j.multra.2022.100005
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Abstract

On-ramp merging areas are deemed to be typical bottlenecks for freeway networks due to the intensive disturbances induced by the frequent merging, weaving, and lane-changing behaviors. The Connected and Autonomous Vehicles (CAVs), benefited from their capabilities of real-time communication and precise motion control, hold an opportunity to promote ramp merging operation through enhanced cooperation. The existing CAV cooperation strategies are mainly designed for single-lane freeways, although multilane configurations are more prevailing in the real-world. In this paper, we present a flow-level CAV coordination strategy to facilitate merging operation in multilane freeways. The coordination integrates lane-change rules between mainstream lanes, proactive creation of large merging gaps, and platooning of ramp vehicles for enhanced benefits in traffic flow stability and efficiency. The strategy is formulated under an optimization framework, where the optimal control plan is determined based on real-time traffic conditions. The impacts of tunable model parameters on the produced control plan are discussed in detail. The efficiency of the proposed multilane strategy is demonstrated in a micro-simulation environment. The results show that the coordination can substantially improve the overall ramp merging efficiency and prevent recurrent traffic congestions, especially under high traffic volume conditions.

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  • The roadway will continue to have mixed traffic with vehicles of different ADS levels for a considerable period.

    “In addition, the roadway will continue to have mixed traffic with vehicles of different ADS levels for a considerable period [2][3][4][5][6][7].”

    From Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic (2024) · cites this paper as [7]

    The Introduction discusses mixed traffic comprising connected and autonomous vehicles (CAVs) and human-driven vehicles, and the Conclusion identifies adapting the strategy to such traffic as future research. Neither passage predicts that mixed traffic will persist for a considerable period or describes a roadway mix of vehicles at different ADS levels. (LLM, conf=0.82)

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Research works printed but not linked: 29

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Cited by

Sorted by citations

Authors
Zhu, J., Tasic, I., & Qu, X.
Affiliations
Chalmers University of Technology (SE)
Corresponding author
Qu, Xiaobo
ORCID
Venue
Multimodal Transportation
Publisher
Elsevier BV
Published
2022-03
Volume
1
Issue
1
Pages
100005
ISSN
2772-5863 (ISSN-L)
DOI
10.1016/j.multra.2022.100005
OpenAlex
W4220728241
Cited by
88
References
0
Citations by year
2026: 16 · 2025: 20 · 2024: 29 · 2023: 19 · 2022: 4
FWCI
7.25
Type
journal article
Language
en
Open access
Licence
Locations
  • Multimodal Transportation (publishedVersion, cc-by-nc-nd)
  • arXiv (Cornell University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Chalmers Research (Chalmers University of Technology) (submittedVersion)
  • arXiv (Cornell University)
Funders
Chalmers Tekniska Högskola
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
  • Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
  • Social Sciences › Transportation › Transportation Planning and Optimization
Keywords
connected and autonomous vehicles, on-ramp merging, lane-changing rules, vehicle platooning, traffic flow stability, traffic congestion reduction, real-time traffic control, freeway bottlenecks

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