The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line
The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passeng...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2016-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/7084353 |
id |
doaj-4440b674120447dd9995ee0eb522d841 |
---|---|
record_format |
Article |
spelling |
doaj-4440b674120447dd9995ee0eb522d8412020-11-24T23:20:34ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/70843537084353The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban LineXiaobing Ding0Xuechen Yang1Hua Hu2Zhigang Liu3Hanchuan Pan4College of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaThe suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system.http://dx.doi.org/10.1155/2016/7084353 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaobing Ding Xuechen Yang Hua Hu Zhigang Liu Hanchuan Pan |
spellingShingle |
Xiaobing Ding Xuechen Yang Hua Hu Zhigang Liu Hanchuan Pan The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line Mathematical Problems in Engineering |
author_facet |
Xiaobing Ding Xuechen Yang Hua Hu Zhigang Liu Hanchuan Pan |
author_sort |
Xiaobing Ding |
title |
The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
title_short |
The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
title_full |
The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
title_fullStr |
The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
title_full_unstemmed |
The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
title_sort |
optimization of passengers’ travel time under express-slow mode based on suburban line |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2016-01-01 |
description |
The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system. |
url |
http://dx.doi.org/10.1155/2016/7084353 |
work_keys_str_mv |
AT xiaobingding theoptimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT xuechenyang theoptimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT huahu theoptimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT zhigangliu theoptimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT hanchuanpan theoptimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT xiaobingding optimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT xuechenyang optimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT huahu optimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT zhigangliu optimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline AT hanchuanpan optimizationofpassengerstraveltimeunderexpressslowmodebasedonsuburbanline |
_version_ |
1725574525691625472 |