Scholarlink

This vision paper presents a prospective architecture for the phased deployment of intelligent and connected vehicle (ICV) systems under mixed traffic conditions. We propose a Vehicle–Road–Cloud–Human (VRCH) integrated architecture to address key technical and socio-technical challenges in autonomous mobility, including edge-case handling, behavioral predictability, and infrastructure compatibility. The architecture reallocates decision-making across distributed roadside infrastructure and cloud services to reduce vehicle-side burden, while ensuringsafety, efficiency and user trust. A phased deployment roadmap for Dedicated Autonomous Lanes (DALs) is introduced, featuring digitally credentialed access, in-transit transition mechanisms (ITTM). Emphasizing human-machine interaction during mode transitions, the framework supports scalable, cost-effective deployment without capital-intensive infrastructure overhaul. Future work includes pilot zone deployment, infrastructure co-design, and scenario-based validation to support the evolution to realize a robust, human-centered intelligent transport systems (ITS) ecosystem.

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Dedicated Lanes for Intelligent and Connected Vehicles in Mixed Traffic

  • 会议论文

  • 发表日期：

    2026年

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  • Yiqun Zhou,
  • Huimin Zhao,
  • Giandomenico Caruso

摘要

This vision paper presents a prospective architecture for the phased deployment of intelligent and connected vehicle (ICV) systems under mixed traffic conditions. We propose a Vehicle–Road–Cloud–Human (VRCH) integrated architecture to address key technical and socio-technical challenges in autonomous mobility, including edge-case handling, behavioral predictability, and infrastructure compatibility. The architecture reallocates decision-making across distributed roadside infrastructure and cloud services to reduce vehicle-side burden, while ensuringsafety, efficiency and user trust. A phased deployment roadmap for Dedicated Autonomous Lanes (DALs) is introduced, featuring digitally credentialed access, in-transit transition mechanisms (ITTM). Emphasizing human-machine interaction during mode transitions, the framework supports scalable, cost-effective deployment without capital-intensive infrastructure overhaul. Future work includes pilot zone deployment, infrastructure co-design, and scenario-based validation to support the evolution to realize a robust, human-centered intelligent transport systems (ITS) ecosystem.