Proactive integrated traffic control to mitigate congestion at toll plazas

Toll plazas on expressways often experience congestion owing to the imbalance between traffic demand and supply. To address this issue, this paper designs a proactive traffic control method to relieve congestion at toll plazas based on the model predictive control (MPC) that integrates the dynamic lane configuration, that is, the numbers of electronic toll collection (ETC) and manual toll collection (MTC) lanes, and the variable speed limit (VSL). The proposed method first forecasts short‐term traffic demand in toll plazas based on the long short‐term memory neural network. Then the cell transmission model (CTM) is applied to predict the traffic evolutions in the toll plaza area. At last, the MPC‐based control framework is used to optimize the numbers of ETC and MTC lanes and the variable speed limit to minimize the total vehicle travel time in a rolling horizon. Micro‐simulation tests are carried out in VISSIM to verify the effectiveness of the proposed control method. The simulation results show that the proposed control method can significantly improve the traffic performances at the toll plazas. The findings in this study can lead to field implementation of proactive control at toll plazas. Toll plazas on expressways often experience congestion during peak hours caused by the imbalance between traffic demand and supply. As a proactive control measure, dynamic lane configuration can adjust traffic supply, and VSL can regulate traffic demand. This study designed an MPC‐based proactive traffic control method that integrated dynamic lane configuration and VSL to relieve congestion at toll plazas.