A survey on dedicated lane management for connected autonomous vehicles in mixed traffic flow

The emergence of connected autonomous vehicles (CAVs) represents a transformative shift in transportation systems, promising enhanced road safety, improved traffic efficiency, and reduced environmental impact. However, the transition period, characterized by mixed traffic flows comprising both human-driven vehicles (HDVs) and CAVs, presents unique challenges for traffic management. Dedicated lane (DL) management strategies have emerged as a critical approach to facilitate the integration of CAVs into existing transportation infrastructure while optimizing overall network performance. This survey systematically examines the state-of-the-art research on DL management for CAVs in mixed traffic environments. Through a rigorous analysis of 160 peer-reviewed publications spanning from 2016 to 2025, this survey synthesizes key findings across multiple dimensions, including traffic flow modeling, lane management strategies, intersection control mechanisms, and network-level optimization approaches. The paper provides a critical evaluation of existing methodologies, identifies research gaps, and outlines future directions for advancing the field. The findings offer valuable insights for transportation planners, traffic management authorities, and researchers working to realize the potential benefits of CAV technology in mixed traffic environments.