Ramp Metering with Microscopic Gap Detection Algorithm Design and Empirical Acceleration Verification

Abstract

Freeway on-ramp areas are susceptible to traffic congestion during peak hours. To delay or prevent the onset of congestion, ramp metering can be applied. A Ramp Metering Installation (RMI) controls the inflow from the on-ramp to the main line so that the total flow can be kept just below capacity. Current ramp metering algorithms apply macroscopic traffic characteristics, which do not entirely prevent inefficient merging behavior from occurring. This paper presents a microscopic ramp metering approach based on gap detection in the right-hand lane of the main line. As preparation for the analyses, trajectory data were collected, by which the mean and standard deviation of driver accelerations were calculated. Simulation, including driver acceleration, is used to test the ramp metering controller. Overall, it shows travel-time savings compared with no-control and compared with existing macroscopic ramp metering systems. Especially during periods of very high main line demand, the microscopic control approach is able to achieve additional travel-time savings. This way, the proposed algorithm can contribute to more efficient road usage and shorter travel times.