Zone-Based Lane-Change Guidance Strategy for Dedicated Lane with a Downstream Incident

This paper focuses on partitioning a zone-based lane-change guidance strategy for a connected and autonomous vehicle-dedicated lane (CAV-DL) in mixed traffic flow when an incident happens downstream of the DL. This study divides the corresponding section into three zones: coordination zone, approach zone, and nearby incident zone. Within these zones, CAVs exhibit different lane change (LC) criteria by considering the requirement of safety and lane change efficiency. Multi-lane cell transmission model (ML-CTM) considering mixed flow is applied to capture the traffic evolutions resulting from the guided LC of CAVs. An optimization model is designed to obtain the optimal setups of guidance LC zone with minimum travel delay under different traffic conditions. The proposed study is validated through Python program simulations, and the results indicate that the optimization model can effectively identify optimal guidance zones with minimum delay.