No abstract

The tunnels are usually natural bottlenecks due to the changes in gradient, which is known as sag. Once a queue propagates from the sag to upstream bottleneck, the induced multi-bottleneck congestion shows a more complicated pattern than an isolated one. In this paper, the congestion pattern of the long-queued tunnel sag is empirically investigated in Shanghai. Three distinctive congestion stages are observed from day-today traffic flow data. The mechanisms of congestion are discussed. Based on the understanding of the congestion pattern, a novel control strategy is proposed which cooperatively controls the tunnel sag mainline and the on-ramp. The control objective is to maximize the throughput and minimize the breakdown probability using quantitative risk analysis method. The control strategy is validated in the field experiment. The traffic features (volume, speed, and productivity) in the tunnel sag are found to be significantly enhanced by the control.