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):  
2014 ◽  
Vol 587-589 ◽  
pp. 1809-1812
Author(s):  
Yue Meng ◽  
Jian Zhang ◽  
Jian Qiang Nie ◽  
Gang Zhong

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.


Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 780 ◽  
Author(s):  
Zihan Qu ◽  
Shiwei He

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.


Author(s):  
J. W. Li ◽  
Y. Ma ◽  
J. W. Jiang ◽  
W. D. Chen ◽  
N. Yu ◽  
...  

Abstract. Starting from the object-oriented idea, this paper analyses the existing event-based models and the logical relationship between behavioral cognition and events, and discusses the continuity of behavioral cognition on the time axis from the perspective of temporal and spatial cognition. A geospatial data model based on behavioral-event is proposed. The physical structure and logical structure of the model are mainly designed, and the four-dimensional model of “time, space, attribute and event” is constructed on the axis. The organic combination of the four models can well describe the internal mechanism and rules of geographical objects. The expression of data model based on behavior-event not only elaborates the basic information of geospatial objects, but also records the changes of related events caused by the changes of geographic Entities' behavior, and expresses the relationship between spatial and temporal objects before and after the changes of behavior cognition. This paper also designs an effective method to organize spatio-temporal data, so as to realize the effective management and analysis of spatio-temporal data and meet the requirements of storage, processing and mining of large spatio-temporal data.


Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4415
Author(s):  
Hak-Ju Lee ◽  
Byeong-Chan Oh ◽  
Seok-Woong Kim ◽  
Sung-Yul Kim

Reliability is an important index which determines the power service and quality provided to customers. As the demand increases continuously and the system changes in accordance with the environmental regulation, the reliability assessment in the distribution system becomes crucial. In this paper, we propose methods for improving the reliability of the distribution system using electric vehicles (EVs) in the system. In this paper, EVs are used as power supplying devices, such as a transportable energy storage system (ESS) which supplies power when fault occurs in the system, and by using a time–space network (TSN) in particular, EV capacity in accordance with the load arrival time was calculated. Unlike other existing reliability assessments, we did not use the average load of customers. Instead, by taking into account the load pattern by times, we considered the priority for load supply in accordance with the failure scenarios and failure times. Based on the priority calculated for each time of failure and failure scenario, plans for EV operation to minimize expected customer interruption cost (ECOST), the reliability index in the distribution system, were established. Finally, a case study was performed using the IEEE RBTS (Roy Billinton Test System) 2 Bus and the performance of the model proposed in this paper was verified based on the result.


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