Tidal Lane Control Method for Highway Toll Plazas Adapting to Strongly Time-Varying Traffic Flow

This study proposes a minute-level tidal lane control framework for highway toll plazas operating under strongly time-varying and directionally imbalanced demand. Historical and real-time traffic volumes, lane-specific service rates, holiday indicators, and weather variables are used to generate 30-min-ahead directional flow forecasts with a Transformer–bidirectional long short-term memory model. The forecasts are then combined with overload-risk screening and a directional-imbalance measure based on the volume-to-capacity ratio to determine whether lane reversal should be implemented. Using field data from a major highway toll plaza in China, the proposed intelligent tidal lane control method reduces average travel time by about 20% during the morning peak and 22% during the evening peak relative to the traditional reactive strategy, with larger gains under high-demand tidal-surge conditions and limited unnecessary intervention under low-demand conditions. The study also provides calibration guidance and recommended ranges for the key thresholds α and d, offering a transferable parameter-calibration procedure and practical guidance for real-world toll-plaza operations.