License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.45
URN: urn:nbn:de:0030-drops-189404
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18940/
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Karikari, Elliot ; Prédhumeau, Manon ; Baudains, Peter ; Manley, Ed

National-Scale Spatiotemporal Variation in Driver Navigation Behaviour and Route Choice (Short Paper)

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Abstract

Understanding human behaviour is an integral task in GIScience, facilitated by increasingly large and descriptive datasets on human activity. Large-scale trajectory data have been particularly useful in measuring behaviours in different contexts, and understanding the relationship between the built environment and people. Yet, to date, most of these studies have focused on urban or regional scale analyses, with less exploration of behavioural variation at larger spatial scales. Human navigation behaviour is inherently linked to variation in spatial structure, and a study of national variations could help to better understand this variability. In this paper, we analyse GPS data from over 1 million journeys by 50,000 connected cars across the UK. Some key statistics relating to route choice are computed, and their variations are explored over time and space. A k-mean clustering of the trips identifies different types of trips and shows that their distribution varies by time of day and across the country. The insights gained from the data highlight spatio-temporal variations in road navigation, which should be considered in transportation modelling and planning.

BibTeX - Entry

@InProceedings{karikari_et_al:LIPIcs.GIScience.2023.45,
  author =	{Karikari, Elliot and Pr\'{e}dhumeau, Manon and Baudains, Peter and Manley, Ed},
  title =	{{National-Scale Spatiotemporal Variation in Driver Navigation Behaviour and Route Choice}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{45:1--45:6},
  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/opus/volltexte/2023/18940},
  URN =		{urn:nbn:de:0030-drops-189404},
  doi =		{10.4230/LIPIcs.GIScience.2023.45},
  annote =	{Keywords: Connected Car, Geospatial big Data, Navigation Behaviour, Cluster Analysis}
}

Keywords: Connected Car, Geospatial big Data, Navigation Behaviour, Cluster Analysis
Collection: 12th International Conference on Geographic Information Science (GIScience 2023)
Issue Date: 2023
Date of publication: 07.09.2023

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