Search Results

Documents authored by Zhao, Qunshan

Document
Complete Volume
DOI: 10.4230/LIPIcs.GIScience.2023
LIPIcs, Volume 277, GIScience 2023, Complete Volume

Authors: Roger Beecham, Jed A. Long, Dianna Smith, Qunshan Zhao, and Sarah Wise

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
LIPIcs, Volume 277, GIScience 2023, Complete Volume
Cite as

12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 1-740, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@Proceedings{beecham_et_al:LIPIcs.GIScience.2023,
  title =	{{LIPIcs, Volume 277, GIScience 2023, Complete Volume}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{1--740},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023},
  URN =		{urn:nbn:de:0030-drops-188945},
  doi =		{10.4230/LIPIcs.GIScience.2023},
  annote =	{Keywords: LIPIcs, Volume 277, GIScience 2023, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.GIScience.2023.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Roger Beecham, Jed A. Long, Dianna Smith, Qunshan Zhao, and Sarah Wise

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 0:i-0:xxiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{beecham_et_al:LIPIcs.GIScience.2023.0,
  author =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{0:i--0:xxiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.0},
  URN =		{urn:nbn:de:0030-drops-188950},
  doi =		{10.4230/LIPIcs.GIScience.2023.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.29
Understanding the Complex Behaviours of Electric Vehicle Drivers with Agent-Based Models in Glasgow (Short Paper)

Authors: Zixin Feng, Qunshan Zhao, and Alison Heppenstall

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
With the new policy aimed at advancing the phase-out date for the sale of new petrol and diesel cars and vans to 2030, the electric vehicle (EV) market share is expected to rise significantly in the coming years. This necessitates a deeper understanding of the driving and charging behaviours of EV drivers to accurately estimate future charging demand distribution and benefit for future infrastructure development. Traditional data-based approaches are limited in illustrating the granular spatiotemporal dynamics of individuals. Recent studies that use conventional vehicle trajectory data also have the sampling bias problem, despite their analyses being conducted at a finer resolution. Moreover, studies that use simulation approaches are often either based on limited behaviour rules for EV drivers or implemented in an artificial grid environment, showing limitations in reflecting real-world situations. To address the challenges, this work introduces an agent-based model (ABM) with complex behaviour rules for EV drivers, taking into account the drivers’ sensitivities to financial and time costs, as well as route deviation. By integrating the simulation model with the origin and destination information of drivers, this work can contribute to a better understanding of the behaviour patterns of EV drivers.
Cite as

Zixin Feng, Qunshan Zhao, and Alison Heppenstall. Understanding the Complex Behaviours of Electric Vehicle Drivers with Agent-Based Models in Glasgow (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 29:1-29:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{feng_et_al:LIPIcs.GIScience.2023.29,
  author =	{Feng, Zixin and Zhao, Qunshan and Heppenstall, Alison},
  title =	{{Understanding the Complex Behaviours of Electric Vehicle Drivers with Agent-Based Models in Glasgow}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{29:1--29:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.29},
  URN =		{urn:nbn:de:0030-drops-189243},
  doi =		{10.4230/LIPIcs.GIScience.2023.29},
  annote =	{Keywords: Electric vehicles, agent-based modelling, charging demand, route choices}
}
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact