Exploring the Congestion Pattern at Long-Queued Tunnel Sag and Increasing the Efficiency by Control

Abstract

The cross-river tunnel is an important facility for modern cities. It is usually a natural bottleneck 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 more complicated pattern than an isolated one. The lack of understanding on such congestion pattern hampers the application of appropriate control strategies. In this paper, the congestion pattern of the long-queued tunnel sag is investigated at the Xiangyin Tunnel in Shanghai. Three distinctive congestion stages are observed from day-to-day 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.