Adapting Ramp Metering Control for Mixed Autonomy Traffic

The introduction of automated vehicles (AVs) is expected to transform traffic dynamics significantly, necessitating new control strategies. Although AVs have potential benefits in terms of improved traffic flow, early versions of AVs, such as adaptive cruise control (ACC) vehicles may have disruptive impacts on traffic flow, which motivates the development of new traffic control strategies. Prior work has demonstrated that an extended ramp metering control algorithm is efficient in regulating traffic at different market penetration rates of automated vehicles in theory. However, it remains unclear whether the proposed control algorithm is effective for implementation. In this study, we analyze how mixed-autonomy traffic affects the performance of ramp metering by simulating the control algorithm on a Minneapolis on-ramp site. Our simulation results show that a higher market penetration rate of ACC vehicles can diminish traffic flow efficiency, while AVs show potential improvements in traffic flow dynamics. Furthermore, we propose adjustments to the algorithm parameters that improves mainline traffic flow conditions while significantly reducing ramp waiting times in different mixed autonomy traffic scenarios. The findings of this study offer insights into adaptable traffic management strategies for mixed-autonomy traffic.