Research on lane-level intelligent control strategies under multi-lane failure scenarios

Active traffic management has become the mainstream means of road traffic control under the environment of vehicle-road coordination and gradually develops towards the direction of refined control. This study focuses on the occurrence of multi-lane failure on highways and how to divide the traffic flow upstream of the failure zone into lanes to limit the speed. It explores the lane-level speed limit control problems under different lane failure scenarios. To improve road access efficiency and safety and alleviate the traffic congestion caused by road failure. First, a multi-lane variable speed limit METANET model is established, and the lane-changing decision-making behaviors of networked vehicles and manual vehicles are integrated to obtain a cooperative control model for mixed traffic flow scenarios. Multiple speed limit strategies are delineated to compare the effect of control strategies under different lane failure scenarios. Results show that: The 90-80km/h speed limit strategy improves the congestion recovery time and exceeds the positive impacts of other speed limit scenarios. Comparative analysis of temporal and spatial speed maps exposes the reasons for this effect.