Integrated Control Strategy of CAV-Dedicated Lane Balancing Efficiency and Safety in Expressway Merging Areas

To alleviate traffic congestion caused by on-ramp vehicles merging into the mainline in expressway merging areas under connected and automated vehicle (CAV) dedicated lane settings, an integrated entry speed adjustment–merging game control (ESA-MGC) control strategy is proposed. This strategy combines on-ramp ESA and CAV-dedicated lane MGC. The ESA strategy dynamically adjusts vehicle speed to proactively create merging gaps, improving on-ramp CAV efficiency, while the MGC strategy employs a game-theoretic approach to coordinate multiple CAVs merging into the dedicated lanes, resolving decision conflicts and optimizing space for on-ramp vehicles. Results show that ESA improves the lane change success rate by 19.23% compared to the gap acceptance model and by 6.82% compared to model predictive control. Under varying CAV penetration rates, MGC improves overall speed by at least 24.26% and reduces the overall time integrated time-to-collision by at least 7.57%. Sensitivity analysis confirms robust performance even at 85% compliance rate, demonstrating significant improvements in traffic efficiency and safety.