Transit Scheduling Model Research Based on Time-Space Network

2014 ◽  
Vol 587-589 ◽  
pp. 1809-1812
Author(s):  
Yue Meng ◽  
Jian Zhang ◽  
Jian Qiang Nie ◽  
Gang Zhong
Keyword(s):  
Optimization Problem ◽  
Minimum Cost ◽  
Schedule Optimization ◽  
Space Network ◽  
Model Based ◽  
Scheduling Model ◽  
Time Space ◽  
Model Research ◽  
Time Table ◽  
Transit Scheduling

This paper try to develop a transit scheduling model based on the time-space network. The object is using the minimum cost to finish the required trips in time-table with the consideration of certain assumptions and rules. In this paper we deal with the multi-depot vehicle schedule optimization problem, addressed as MDVSP, using one time-space network instead of the traditional connection-based networks. Furthermore, we introduce the concept of open-depot, which means the bus may not return the depot where it started.

scholarly journals Development of the commuter demand concentration model based on a time-space network scheme.

2002 ◽  
pp. 65-79 ◽  
Author(s):  
Hitoshi IEDA ◽  
Kazuyuki TSUCHIYA ◽  
Le Binh PHAN ◽  
Toshiyuki OKAMURA
Keyword(s):  
Space Network ◽  
Model Based ◽  
Time Space

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

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 780 ◽  
Author(s):  
Zihan Qu ◽  
Shiwei He
Keyword(s):  
Network Model ◽  
Traffic Congestion ◽  
Flow Distribution ◽  
Distribution Model ◽  
A Algorithm ◽  
Traffic Forecasting ◽  
Space Network ◽  
Model Based ◽  
Time Space ◽  
Feasible Path

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.

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