Suitability Evaluation of a Train’s Scheduled Section Travel Time
Two methods used to evaluate the suitability of a train’s scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an...
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doaj-5bc3eb834a584346844b4830ecd369d22020-11-25T02:32:09ZengMDPI AGSustainability2071-10502020-03-01126239910.3390/su12062399su12062399Suitability Evaluation of a Train’s Scheduled Section Travel TimeMaosheng Li0Qing Huang1Lixuan Yao2Yongliang Wang3School of traffic and transportation engineering, Central South University, Changsha 410083, ChinaSchool of traffic and transportation engineering, Central South University, Changsha 410083, ChinaSchool of traffic and transportation engineering, Central South University, Changsha 410083, ChinaSchool of traffic and transportation engineering, Central South University, Changsha 410083, ChinaTwo methods used to evaluate the suitability of a train’s scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an instruction of TSSTT in cases where the train operation data are provided. A suitability evaluation method of TSSTT is proposed by calculating the possibility that a train completes a task within the time windows, centering on the TSSTT given in advance. The TSRTs between two adjacent stations are classified into four groups based on whether the train dwells at the two end stations of the railway section, and then subdivided secondly into subgroups by the instruction of TSSTT given. The kurtosis of each subgroup data of TSRT is larger than 3, so Weibull distribution is selected to fit the TSRT distribution of subgroup data due to good fitness based on root measurement of the least square (SRLSM). A busy high-speed railway line in the Wuhan area of China is used to validate the presented approach. Each railway section has its own suitable TSSTT in which TSRT might achieve 96% reliability of arriving within 2.5 minutes centering on suitable TSSTT, otherwise which might not obtain 10% reliability.https://www.mdpi.com/2071-1050/12/6/2399suitabilityreliabilitytrain’s scheduled section travel timetrain section running time |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maosheng Li Qing Huang Lixuan Yao Yongliang Wang |
spellingShingle |
Maosheng Li Qing Huang Lixuan Yao Yongliang Wang Suitability Evaluation of a Train’s Scheduled Section Travel Time Sustainability suitability reliability train’s scheduled section travel time train section running time |
author_facet |
Maosheng Li Qing Huang Lixuan Yao Yongliang Wang |
author_sort |
Maosheng Li |
title |
Suitability Evaluation of a Train’s Scheduled Section Travel Time |
title_short |
Suitability Evaluation of a Train’s Scheduled Section Travel Time |
title_full |
Suitability Evaluation of a Train’s Scheduled Section Travel Time |
title_fullStr |
Suitability Evaluation of a Train’s Scheduled Section Travel Time |
title_full_unstemmed |
Suitability Evaluation of a Train’s Scheduled Section Travel Time |
title_sort |
suitability evaluation of a train’s scheduled section travel time |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-03-01 |
description |
Two methods used to evaluate the suitability of a train’s scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an instruction of TSSTT in cases where the train operation data are provided. A suitability evaluation method of TSSTT is proposed by calculating the possibility that a train completes a task within the time windows, centering on the TSSTT given in advance. The TSRTs between two adjacent stations are classified into four groups based on whether the train dwells at the two end stations of the railway section, and then subdivided secondly into subgroups by the instruction of TSSTT given. The kurtosis of each subgroup data of TSRT is larger than 3, so Weibull distribution is selected to fit the TSRT distribution of subgroup data due to good fitness based on root measurement of the least square (SRLSM). A busy high-speed railway line in the Wuhan area of China is used to validate the presented approach. Each railway section has its own suitable TSSTT in which TSRT might achieve 96% reliability of arriving within 2.5 minutes centering on suitable TSSTT, otherwise which might not obtain 10% reliability. |
topic |
suitability reliability train’s scheduled section travel time train section running time |
url |
https://www.mdpi.com/2071-1050/12/6/2399 |
work_keys_str_mv |
AT maoshengli suitabilityevaluationofatrainsscheduledsectiontraveltime AT qinghuang suitabilityevaluationofatrainsscheduledsectiontraveltime AT lixuanyao suitabilityevaluationofatrainsscheduledsectiontraveltime AT yongliangwang suitabilityevaluationofatrainsscheduledsectiontraveltime |
_version_ |
1724821189392596992 |