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The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution
Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air polluti...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690490/ https://www.ncbi.nlm.nih.gov/pubmed/36429848 http://dx.doi.org/10.3390/ijerph192215128 |
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author | Zhao, Zilong Fang, Mengyuan Tang, Luliang Yang, Xue Kan, Zihan Li, Qingquan |
author_facet | Zhao, Zilong Fang, Mengyuan Tang, Luliang Yang, Xue Kan, Zihan Li, Qingquan |
author_sort | Zhao, Zilong |
collection | PubMed |
description | Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, we propose a complete framework to quantitatively assess the positive impacts of community shuttle services, including route design, traffic congestion alleviation, and air pollution reduction. During the design of community shuttle services, we developed a novel method to adaptively generate shuttle stops with maximum service capacity based on residents’ origin–destination (OD) data, and designed shuttle routes with minimum mileage by genetic algorithm. For traffic congestion alleviation, we identified trips that can be shifted to shuttle services and their potential changes in traffic flow. The decrease in traffic flow can alleviate traffic congestion and indirectly reduce unnecessary pollutant emissions. In terms of environmental protection, we utilized the COPERT III model and the spatial kernel density estimation method to finely analyze the reduction in traffic emissions by eco-friendly transportation modes to support detailed policymaking regarding transportation environmental issues. Taking Chengdu, China as the study area, the results indicate that: (1) the adaptively generated shuttle stops are more responsive to the travel demands of crowds compared with the existing bus stops; (2) shuttle services can replace 30.36% of private trips and provide convenience for 50.2% of commuters; (3) such eco-friendly transportation can reduce traffic emissions by 28.01% overall, and approximately 42% within residential areas. |
format | Online Article Text |
id | pubmed-9690490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96904902022-11-25 The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution Zhao, Zilong Fang, Mengyuan Tang, Luliang Yang, Xue Kan, Zihan Li, Qingquan Int J Environ Res Public Health Article Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, we propose a complete framework to quantitatively assess the positive impacts of community shuttle services, including route design, traffic congestion alleviation, and air pollution reduction. During the design of community shuttle services, we developed a novel method to adaptively generate shuttle stops with maximum service capacity based on residents’ origin–destination (OD) data, and designed shuttle routes with minimum mileage by genetic algorithm. For traffic congestion alleviation, we identified trips that can be shifted to shuttle services and their potential changes in traffic flow. The decrease in traffic flow can alleviate traffic congestion and indirectly reduce unnecessary pollutant emissions. In terms of environmental protection, we utilized the COPERT III model and the spatial kernel density estimation method to finely analyze the reduction in traffic emissions by eco-friendly transportation modes to support detailed policymaking regarding transportation environmental issues. Taking Chengdu, China as the study area, the results indicate that: (1) the adaptively generated shuttle stops are more responsive to the travel demands of crowds compared with the existing bus stops; (2) shuttle services can replace 30.36% of private trips and provide convenience for 50.2% of commuters; (3) such eco-friendly transportation can reduce traffic emissions by 28.01% overall, and approximately 42% within residential areas. MDPI 2022-11-16 /pmc/articles/PMC9690490/ /pubmed/36429848 http://dx.doi.org/10.3390/ijerph192215128 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhao, Zilong Fang, Mengyuan Tang, Luliang Yang, Xue Kan, Zihan Li, Qingquan The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title | The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title_full | The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title_fullStr | The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title_full_unstemmed | The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title_short | The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution |
title_sort | impact of community shuttle services on traffic and traffic-related air pollution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9690490/ https://www.ncbi.nlm.nih.gov/pubmed/36429848 http://dx.doi.org/10.3390/ijerph192215128 |
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