Abstract
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.
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
Open research fund program of LIESMARS, Wuhan university
Subject
Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health
Reference57 articles.
1. Integrated Transport System of the South-Moravian Region and its impact on rural development;Vaishar;Transp. Res. Part D-Transp. Environ.,2015
2. Optimal design of community shuttles with an adaptive-operator-selection-based genetic algorithm;Xiong;Transp. Res. Part C: Emerg. Technol.,2021
3. Kan, Z., Tang, L., Kwan, M.-P., and Zhang, X. (2018). Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data. Int. J. Environ. Res. Public Health, 15.
4. Ministry of Ecology and Environment of the People’s Republic of China (2021). China Mobile Source Environmental Management Annual Report, Ministry of Ecology and Environment of the People’s Republic of China.
5. Quantifying and analyzing traffic emission reductions from ridesharing: A case study of Shanghai;Yan;Transp. Res. Part D Transp. Environ.,2020