A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency

Zihan Qu,Shiwei He

doi:10.3390/sym11060780

Abstract

Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time-space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion.

Highlights

IntroductionThe Description of the Subject of Research and the Motives to Take
One of the sub-problems is the construction of a time-space network based on the turnover process of railcar and transition of railcar state, the other sub-problem is the construction of a dynamic railcar flow distribution model in an emergency
Because loaded railcar flow has the characteristics of a tree path, this paper describes the transport time-space arcs that satisfy of atime continuity

Summary

Introduction

The Description of the Subject of Research and the Motives to Take. When the station in a transportation network stops operation due to natural disasters and other emergencies, trains cannot pass through the station. Trains arriving or passing through the station have to be rerouted. As there are capacity limitation stations in the transportation network, after a period of time, the railcar flow in some of the other stations will become overstocked, forming congestion. The congestion will greatly reduce the network’s transport capacity. Failure to timely predict the congestion will result in propagation of congestion and even the paralysis of the transportation network

Methods

Results

Conclusion