A Ramp Metering Method Based on Congestion Status in the Urban Freeway

In ramp metering methods, the ALINEA algorithm is a very effective way and has been applied widely. But the critical occupancy in ALINEA algorithm is often difficult to obtain and not particularly accurate. It will greatly affect the performance of ALINEA algorithm. In this paper, an improved ALINEA algorithm, named CS-ALINEA, is proposed. In this method, the traffic flow is used to replace the occupancy as the control parameter and the control rate can be selected according to the congestion status reclassified adaptively. In the existing ramp control methods, to guarantee the traffic efficiency of mainstream, the impact of ramp overflow on ground road traffic is often ignored. In order to resolve this issue, the segmented control method is adopted in this paper. When the ramp queuing length exceeds the critical queue length, the signal timing scheme is adjusted by selecting the control rate to avoid the ramp overflow. The SUMO simulation platform is used to simulate the ramp control and test the CS-ALINEA algorithm. The experimental results show that the proposed method can optimize the ramp queuing length and reduce waiting time of vehicles while the efficiency of urban freeway can be guaranteed.