Please use this identifier to cite or link to this item:
DC FieldValueLanguage
dc.contributor.authorZhuge, Cen_US
dc.contributor.authorShao, Cen_US
dc.contributor.authorLi, Xen_US
dc.identifier.citationEnergies, 2019, v. 12, no. 16, 3073en_US
dc.description.abstractAn empirical study of the parking behaviour of Conventional Vehicles (CVs), Battery Electric Vehicles (BEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) was carried out with the data collected in a paper-based questionnaire survey in Beijing, China. The study investigated the factors that might influence the parking behaviour, with a focus on the maximum acceptable time of walking from parking lot to trip destination, parking fee, the availability of charging posts, the state of charge of EVs and the range anxiety of BEVs. Several Multinomial Logit (MNL) models were developed to explore the relationships between individual attributes and parking choices. The results suggest that (1) the maximum acceptable walking time generally increases with the rise in the amount of saving for parking fee; (2) the availability of charging posts does not influence the maximum acceptable walking time when PHEVs and BEVs have sufficient charge, but the percentage of people willing to walk longer than eight minutes increases from around 35% to 46% when PHEVs are in a low stage of charge; (3) more than half of BEV drivers want the driving range of their vehicles to be one and a half times the driving distance before they depart, given the distance is 50 km. Based on the empirical findings above, a conceptual framework was proposed to explicitly simulate the parking behaviour of both CVs and EVs using agent-based modelling.en_US
dc.description.sponsorshipDepartment of Land Surveying and Geo-Informaticsen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 by the authors. 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 (
dc.rightsThe following publication Zhuge C, Shao C, Li X. Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China. Energies. 2019; 12(16):3073, is available at
dc.subjectAgent-based modellingen_US
dc.subjectCharging behaviouren_US
dc.subjectElectric vehiclesen_US
dc.subjectMultinomial Logit (MNL) modelen_US
dc.subjectParking behaviouren_US
dc.titleEmpirical analysis of parking behaviour of conventional and electric vehicles for parking modelling : a case study of Beijing, Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.description.validate201910 bcma-
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Zhuge_Empirical_Analysis_Parking.pdf3.33 MBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show simple item record
PIRA download icon_1.1View/Download Contents


Citations as of Nov 30, 2019

Page view(s)

Citations as of Dec 4, 2019


Citations as of Dec 4, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.