An Optimization Method for Joint Control of Merging Zones in Urban Tunnels of Considerable Length

To address traffic congestion at merging zones in urban tunnels of considerable length, an optimization method for joint control that integrates variable speed limits in mainlines and signal control at ramps is proposed. A four-level control strategy is developed based on the combination of different traffic states in merging bottleneck area and downstream section. The traditional meta network (METANET) model is modified by comprehensively considering ramp inflow, speed differences among sections, and driver compliance. Meanwhile, the classical ALINEA algorithm is extended by introducing a control mechanism for queue capacity at ramps, enabling the integration of variable speed limits and ramp signal control. On this basis, a model predictive control approach is employed to optimize speed limits and ramp signal timings under different traffic states. Using the VISSIM simulation platform, the scenario of Lianghu Tunnel in Wuhan is developed, which allows to acquire and control the traffic parameters in real-time through the COM interface and secondary development with Python. Various control strategies are compared, including dynamic variable speed limits, ramp signal control, and joint control. Simulation results show that: ①Compared to the situation with no control, the proposed joint control strategy reduces travel time in the bottleneck area by 17.7% and decreases the average delay time per vehicle by 62.96%. ②Compared to single control strategy, the joint control strategy significantly improves average speed and stability of traffic flow, with especially notable effects under heavy congestion conditions. ③Under the joint control strategy, the minimum average speed at road sections increases by 20.38%, the duration of slow traffic in the bottleneck area and at the downstream section decreases by 22.2%, and both the spatial scope and duration of low-speed regions are significantly reduced with a substantial decrease in speed fluctuations. When facing various complex traffic flow conditions, the joint control strategy demonstrates good dynamic adaptability, automatically adjusting the control strength of the mainline and ramp according to the flow structure, thus achieving a rational distribution of traffic load in the bottleneck area.