Empirical analysis of parking behaviour of conventional and electric vehicles for parking modelling:A case study of Beijing, China

Zhuge, Chengxiang, Shao, Chunfu and Li, Xia (2019) Empirical analysis of parking behaviour of conventional and electric vehicles for parking modelling:A case study of Beijing, China. Energies, 12 (16). ISSN 1996-1073

[thumbnail of energies-12-03073-v2]
PDF (energies-12-03073-v2) - Published Version
Available under License Creative Commons Attribution.

Download (6MB) | Preview


An 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.

Item Type: Article
Uncontrolled Keywords: agent-based modelling,beijing,charging behaviour,electric vehicles,multinomial logit (mnl) model,parking behaviour,renewable energy, sustainability and the environment,energy engineering and power technology,energy (miscellaneous),control and optimization,electrical and electronic engineering,sdg 7 - affordable and clean energy ,/dk/atira/pure/subjectarea/asjc/2100/2105
Faculty \ School: Faculty of Science > School of Environmental Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 12 Sep 2019 14:34
Last Modified: 22 Oct 2022 05:13
URI: https://ueaeprints.uea.ac.uk/id/eprint/72142
DOI: 10.3390/en12163073


Downloads per month over past year

Actions (login required)

View Item View Item