Cargando…
Optimizing a desirable fare structure for a bus-subway corridor
This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strat...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5628816/ https://www.ncbi.nlm.nih.gov/pubmed/28981508 http://dx.doi.org/10.1371/journal.pone.0184815 |
_version_ | 1783268943962570752 |
---|---|
author | Liu, Bing-Zheng Ge, Ying-En Cao, Kai Jiang, Xi Meng, Lingyun Liu, Ding Gao, Yunfeng |
author_facet | Liu, Bing-Zheng Ge, Ying-En Cao, Kai Jiang, Xi Meng, Lingyun Liu, Ding Gao, Yunfeng |
author_sort | Liu, Bing-Zheng |
collection | PubMed |
description | This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. |
format | Online Article Text |
id | pubmed-5628816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56288162017-10-20 Optimizing a desirable fare structure for a bus-subway corridor Liu, Bing-Zheng Ge, Ying-En Cao, Kai Jiang, Xi Meng, Lingyun Liu, Ding Gao, Yunfeng PLoS One Research Article This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. Public Library of Science 2017-10-05 /pmc/articles/PMC5628816/ /pubmed/28981508 http://dx.doi.org/10.1371/journal.pone.0184815 Text en © 2017 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Liu, Bing-Zheng Ge, Ying-En Cao, Kai Jiang, Xi Meng, Lingyun Liu, Ding Gao, Yunfeng Optimizing a desirable fare structure for a bus-subway corridor |
title | Optimizing a desirable fare structure for a bus-subway corridor |
title_full | Optimizing a desirable fare structure for a bus-subway corridor |
title_fullStr | Optimizing a desirable fare structure for a bus-subway corridor |
title_full_unstemmed | Optimizing a desirable fare structure for a bus-subway corridor |
title_short | Optimizing a desirable fare structure for a bus-subway corridor |
title_sort | optimizing a desirable fare structure for a bus-subway corridor |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5628816/ https://www.ncbi.nlm.nih.gov/pubmed/28981508 http://dx.doi.org/10.1371/journal.pone.0184815 |
work_keys_str_mv | AT liubingzheng optimizingadesirablefarestructureforabussubwaycorridor AT geyingen optimizingadesirablefarestructureforabussubwaycorridor AT caokai optimizingadesirablefarestructureforabussubwaycorridor AT jiangxi optimizingadesirablefarestructureforabussubwaycorridor AT menglingyun optimizingadesirablefarestructureforabussubwaycorridor AT liuding optimizingadesirablefarestructureforabussubwaycorridor AT gaoyunfeng optimizingadesirablefarestructureforabussubwaycorridor |