Extending Existing Ramp Metering Control in the Field for Mixed-Autonomy Traffic

Automated vehicles (AVs), including vehicles equipped with adaptive cruise control (ACC), are fundamentally shifting macroscopic traffic flow characteristics, necessitating updates to existing traffic control strategies. This study evaluates a parametric extension of the Minnesota Department of Transportation density-adaptive ramp metering algorithm designed for mixed-autonomy conditions. By tuning critical and jam density thresholds based on market penetration rates, the controller logic was aligned with the specific physical limits of the traffic stream. Simulation results indicated that default metering logic, calibrated for human-driven vehicles (HVs), failed to account for the reduced critical density of commercial ACC vehicles. This mismatch reduced mainline throughput by up to 46.1% under default settings as the controller failed to prevent premature mainline degradation. The proposed adjustment mitigated these impacts by restricting inflow according to the actual, lower density thresholds of the ACC-mixed flow, increasing mainline throughput by up to 5.7% relative to the default implementation. Conversely, in AV scenarios, the adjusted algorithm utilized enhanced roadway capacity to reduce ramp wait times by up to 14.8% while maintaining comparable mainline throughput. The no-meter results further showed that ramp metering remained necessary under both ACC and AV market penetration scenarios. These findings provide a practical framework for optimizing existing metering infrastructure in the transition toward mixed-autonomy traffic.