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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Main Authors: Maosheng Li, Qing Huang, Lixuan Yao, Yongliang Wang
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/6/2399
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spelling 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
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