Simulation Study Based on OpenTrack on Carrying Capacity in District of Beijing-Shanghai High-speed Railway
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1 Applied Mechanics and Materials Online: ISSN: , Vols , pp doi: / Trans Tech Publications, Switzerland Simulation Study Based on OpenTrack on Carrying Capacity in District of Beijing-Shanghai High-speed Railway Zhen Chen 1,a, Baoming Han 1,b 1 School of Traffic and Transportation, Beijing Jiaotong University, Beijing , China a @bjtu.edu.cn, b bmhan@bjtu.edu.cn Keywords: High-speed railway; Carrying capacity; Simulation; OpenTrack. Abstract. The paper simulated the carrying capacity in Nanjing-Shanghai district of Beijing-Shanghai high-speed railway by using OpenTrack software. Firstly, the paper modeled s topological structures and sections topological structures of Beijing-Shanghai high-speed railway and set the parameters for simulation. Secondly, the paper simulated on the condition of current train service frequency no less than the frequency in simulation while the was respectively 3, 4 and 5. Finally, the paper analyzed the carrying capacity in Nanjing-Shanghai district by analyzing the simulation train diagram outputted by OpenTrack. Introduction Beijing-Shanghai high-speed railway is a 1318-kilometers-long railway which is between Beijing South and Shanghai Hongqiao. The design speed of the railway is 350 kilometers per hour and the current train speed is 300 kilometers per hour. Nanjing-Shanghai district is between Nanjing south and Shanghai Hongqiao included some busy passenger s such as Suzhou and Wuxi East. At the first year of the railway beginning operation, the number of passenger originated reached up to 5.26 million. Although Beijing-Shanghai high-speed railway provides a convenient way for passenger to travel, the number of ticket during holidays and festivals is still not enough. Therefore, it is important to enhance the carrying capacity of the high-speed railway to satisfy the increasing demand of passenger trips. There are three common methods for calculating carrying capacity in China including the deduction coefficient method [1,2], the average minimum train spacing interval method [3] and the computer simulation method [4,5]. The deduction coefficient method and the average minimum train spacing interval method have lots of limitation and aim at study on carrying capacity of a single or section. It is difficult for the two methods to study on the carrying capacity of railway network. The computer simulation method is able to overcome the shortage of the two methods. Therefore the computer simulation methods is an appropriate method to study on the carrying capacity of high-speed railway. The paper used OpenTrack software to model and simulate Beijing-Shanghai high-speed railway to study on carrying capacity in Nanjing-Shanghai district. Modeling Beijing-Shanghai high-speed railway in OpenTrack Physical model. Physical model include arrival-departure tracks, signals, turnouts, rolling stock and so on. In OpenTrack, railway s are made up of vertexes, edges and signals. Vertex represent a point where attributes of tracks such as gradient, radius and speed limitation changed or signal was located or turnout was located. Edge link two vertexes as a part of track. Attributes of edges are set as attributes of tracks. Signal is located at the vertex and is an important part of train route settings. The paper used single aspect main signal as home signal and three aspect combined signal as exit signal. All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, (ID: , Pennsylvania State University, University Park, USA-10/05/16,10:01:42)
2 568 Advances in Transportation There were several processes to model the physical model as follows. Firstly, located the point where attributes of tracks changed, signals were located and turnouts were located on the workspace by using the vertex. Secondly, linked the vertexes with edges and set attributes of edges such as gradient, radius and speed limitation. Finally, located signals at vertexes. Figure 1 is the topological structure of Shanghai Hongqiao. Figure 1. Topological structure of Shanghai Hongqiao Logical model. Logical model include route, path and itinerary which control the information of turnouts, tracks that trains pass by. OpenTrack uses three-level data structure to describe railway logical network. The first level of train operation definition in OpenTrack is route. A route consists of a series of successive vertexes and edges. During the simulation process if a route is required by a train, the route will be reserved for the train only if it is not reserved for another train and if an edge belonging to the route is not reserved or occupied. Once the last part of a train has passed the release point of the route, the reserved section is made available for another train after passage of the release time. OpenTrack will automatically find routes in the track layout, and then user review these routes and choose appropriate routes. The second level of train operation definition in OpenTrack is path. Path consist of a series of successive routes in one direction of travel. OpenTrack is able to combine a series of successive routes automatically according to user s demand. The third level of train operation definition in OpenTrack is itinerary. Itinerary is the top level which consist of one or several successive paths. In the simulation process a train is given a list of itineraries with a priority for each itinerary. This list comprises all itineraries on which the train may move. The actual itinerary used by the train is determined during the simulation in that the train always selects the available itinerary with the highest priority. Itinerary tells a train which track the train should pass by, therefore each train should have one or more its own itinerary. OpenTrack is able to choose one paths or successive routes automatically according to user s demand. The paper set routes, paths and itineraries as follows. Routes began and ended at home signal and exit signal in. Paths began at a s exit signal and ended at the next s exit signal. Itineraries began at departure s exit signal, passed by an intermediate s track and ended at terminal s exit signal. Trains would run on the railway following the information in itineraries.
3 Applied Mechanics and Materials Vols Analysis of the carrying capacity in Nanjing-Shanghai district on simulation result The paper chose the up direction of Nanjing-Shanghai district as an example to study on the ultimate carrying capacity in district when the is respectively 5, 4 and 3. The simulation scene was set as follows. The paper used periodic diagram which period is one hour and parallel diagram. The train speed limitation was 300 kilometers per hour and dwelling time at is 2. Train service frequency in simulation is no less than current frequency (shown in Table 1). Time at which trains were able to run on the rail was between 7:00 and 24:00. Simulation train diagram outputted by OpenTrack is shown in Figure 2. And train service frequency of different diagram is shown in Table 1. Figure 2. Simulation result: diagram of 4 in one period (The blue line represented the simulation train path, and the black line represented the planning train path.) Frequency [trains per day] Frequency [trains per hour]/[ trains per day] Table 1. Train service frequency of different diagram. Station name Zhenjiang South Danyang Changzhou Wuxi East Current train diagram Diagram of 5 Diagram of 4 Diagram of 3 Suzhou Kunshan South /32 2/32 4/63 3/48 3/47 2/31 1/16 1/16 2/32 2/32 2/32 2/31 1/16 1/16 2/32 2/32 2/32 2/30
4 570 Advances in Transportation The carrying capacity was 11 trains per hour when the was 5. There were 1 nonstop train, 7 trains stopping once and 3 trains stopping three times. Only the first 10 trains in the period before maintenance time window was able to run. Therefore, the carrying capacity of up direction in the district was =175 trains. The carrying capacity was 14 trains per hour when the was 4. There were 4 nonstop train, 10 trains stopping once. Only the first 13 trains in the period before maintenance time window was able to run. Therefore, the carrying capacity of up direction in the district was =223 trains. The carrying capacity was 19 trains per hour when the was 4. There were 9 nonstop train, 10 trains stopping once. Only the first 17 trains in the period before maintenance time window was able to run. Therefore, the carrying capacity of up direction in the district was =302 trains. Conclusion The paper got the conclusion as follows. The carrying capacity increases by 27.3% when the reduces from 5 to 4. The carrying capacity increases by 35.7% when the reduces from 4 to 3. The carrying capacity increases by 72.7% when the reduces from 5 to 3. Reducing the is an effective method to increasing the carrying capacity. However, the number of dwelling times and dwelling groups reduces with the reducing of the and passengers who have short distance travel demand have only a few choices. On the contrary, carrying capacity reduces with increasing of the number of dwelling times. Therefore, it is important to find a balance among the, the number of dwelling times and the carrying capacity. Functions that the paper had used was only a few part in OpenTrack. In the future, it is possible to add EMU depot, draw-out track and so on in order to simulate the whole system of high-speed railway comprehensively and to provide reliable evidence for operation and management of high-speed railway. Acknowledgements This work was financially supported by the Projects in the National Science & Technology Pillar Program (2009BAG12A10), we would like to thanks the related committee. References [1] Lizhen Zhao, in: China Railway Science, Vol.22 No.6, In Chinese [2] Hongliang Zhang, Hao Yang, in: Railway Transport and Economy, Vol.22, No.6, In Chinese [3] Deyong Wei, Jinyong Wang, Fan Yu, in: Journal of Railway Engineering Society, In Chinese [4] Min Liu, Booming Han, Dewei Li, in: Journal of the China Railway Society, Vol.34, No.4, In Chinese [5] Wen Du, Dong Wen, in: Journal of Southwest Jiaotong University, 2006, 41(5). In Chinese
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