 Comprehensive Public Transport Service Accessibility Index—A New Approach Based on Degree Centrality and Gravity ModelRuqin Yang,
Yaolin Liu,
Yanfang Liu,
Hui Liu and
Wenxia Gan
Sustainability, 2019, vol. 11, issue 20, 1-20 Abstract: Public transport accessibility (PTA) is an essential index for evaluating the efficiency of urban public transport resource and public service. Improving public transport accessibility is considered as the most effective way of alleviating urban congestion and promoting urban sustainability. PTA can be divided into three types, which are access to stations, accessibility of networks and access to activities. This paper focuses on evaluating access to public transport service at stations, considering walking time to stations and waiting time for services at stations. Numerous studies have been carried out on evaluating the accessibility of public transport stations. When building accessibility evaluation model, rare has seen different public transport modes as an integrated system. Hence the topological structure and geometrical layout of the system are not considered. In this paper, factors like the configuration of the public transport system and the surrounding environment of stations are included for the evaluation. The centrality of station index (COS) is presented to describe the importance of stations in the integrated public transport system. The COS index is an improved combination of the gravity model and degree centrality index of the complex network. This index improves the degree centrality index by replacing the number of nodes with weighted connections between stations. By modeling public transport operation, configuration and surroundings of stations, a comprehensive public transport service accessibility index (CPTAI) is formulated to quantify accessibility at the community level. To compute this index, a network analysis model is firstly applied to find the nearest station for each point of interest (POI) by using ArcGIS desktop 10.2, and the transport service frequency at the nearest station is measured. Then Baidu Map API is employed to measure the impedance indexes between stations in the integrated public transport network. Activities covered by stations within a given distance are seen as the generation and attraction of trips in between the stations. Then a weighted gravity model and COS is presented to calculate the integrated service frequency (ISF) for each POI afterward. In the end, the index is converted to the community level, which is CPTAI. The experiment is carried out in Wuhan metropolitan area, Hubei, China. Smart card data (SCD) is utilized to evaluate CPTAI and examine the association between commuting trips by public transport and accessibility level within Wuhan metropolitan area. Experimental results show that CPTAI has a significant statistical association with trips by public transport. Keywords: public transport; accessibility; centrality; CPTAI; Baidu Map API; SCD (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:20:p:5634-:d:275886 Access Statistics for this article Sustainability is currently edited by Ms. Alexandra Wu More articles in Sustainability from MDPI |
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