Modeling of public transport waiting time indicator for the transport network of a large city

The need to develop and improve public passenger transport in major cities was noted. It was reflected that waiting time at bus stops is one of the factors that have a big impact on the passenger quality assessment of transport services. The results of an empirical study of the actual and anticipate...

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Main Authors: Lebedeva Olga, Kripak Marina
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201822404018
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spelling doaj-85482485d56b400cbc952c0a7a1708712021-02-02T00:34:50ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012240401810.1051/matecconf/201822404018matecconf_icmtmte2018_04018Modeling of public transport waiting time indicator for the transport network of a large cityLebedeva Olga0Kripak MarinaFederal State Autonomous Educational Institution of Higher Education «Sevastopol State University»The need to develop and improve public passenger transport in major cities was noted. It was reflected that waiting time at bus stops is one of the factors that have a big impact on the passenger quality assessment of transport services. The results of an empirical study of the actual and anticipated waiting time at bus stops were given. It was noted that the reliability functions were used in the field of ride duration modeling, traffic restoration time after an accident, and length of making the decision to travel. The waiting time distribution functions using the lognormal function and the Weibull function were chosen. The results of modeling were objective, the dependent variables in it were the expected waiting time of passengers and the difference between the anticipated and the actual waiting time. The explanatory variables were sex, age, time period, purpose of the trip and the actual waiting time. The results of the research showed that the age, purpose of the trip and the time period influence the waiting time perception, prolong it and lead to its reassessment.https://doi.org/10.1051/matecconf/201822404018
collection DOAJ
language English
format Article
sources DOAJ
author Lebedeva Olga
Kripak Marina
spellingShingle Lebedeva Olga
Kripak Marina
Modeling of public transport waiting time indicator for the transport network of a large city
MATEC Web of Conferences
author_facet Lebedeva Olga
Kripak Marina
author_sort Lebedeva Olga
title Modeling of public transport waiting time indicator for the transport network of a large city
title_short Modeling of public transport waiting time indicator for the transport network of a large city
title_full Modeling of public transport waiting time indicator for the transport network of a large city
title_fullStr Modeling of public transport waiting time indicator for the transport network of a large city
title_full_unstemmed Modeling of public transport waiting time indicator for the transport network of a large city
title_sort modeling of public transport waiting time indicator for the transport network of a large city
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description The need to develop and improve public passenger transport in major cities was noted. It was reflected that waiting time at bus stops is one of the factors that have a big impact on the passenger quality assessment of transport services. The results of an empirical study of the actual and anticipated waiting time at bus stops were given. It was noted that the reliability functions were used in the field of ride duration modeling, traffic restoration time after an accident, and length of making the decision to travel. The waiting time distribution functions using the lognormal function and the Weibull function were chosen. The results of modeling were objective, the dependent variables in it were the expected waiting time of passengers and the difference between the anticipated and the actual waiting time. The explanatory variables were sex, age, time period, purpose of the trip and the actual waiting time. The results of the research showed that the age, purpose of the trip and the time period influence the waiting time perception, prolong it and lead to its reassessment.
url https://doi.org/10.1051/matecconf/201822404018
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AT kripakmarina modelingofpublictransportwaitingtimeindicatorforthetransportnetworkofalargecity
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