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Documents authored by Xie, Hairuo

Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.7
Introducing Diversion Graph for Real-Time Spatial Data Analysis with Location Based Social Networks

Authors: Sameera Kannangara, Hairuo Xie, Egemen Tanin, Aaron Harwood, and Shanika Karunasekera

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract
Neighbourhood graphs are useful for inferring the travel network between locations posted in the Location Based Social Networks (LBSNs). Existing neighbourhood graphs, such as the Stepping Stone Graph lack the ability to process a high volume of LBSN data in real time. We propose a neighbourhood graph named Diversion Graph, which uses an efficient edge filtering method from the Delaunay triangulation mechanism for fast processing of LBSN data. This mechanism enables Diversion Graph to achieve a similar accuracy level as Stepping Stone Graph for inferring travel networks, but with a reduction of the execution time of over 90%. Using LBSN data collected from Twitter and Flickr, we show that Diversion Graph is suitable for travel network processing in real time.
Cite as

Sameera Kannangara, Hairuo Xie, Egemen Tanin, Aaron Harwood, and Shanika Karunasekera. Introducing Diversion Graph for Real-Time Spatial Data Analysis with Location Based Social Networks. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{kannangara_et_al:LIPIcs.GIScience.2021.I.7,
  author =	{Kannangara, Sameera and Xie, Hairuo and Tanin, Egemen and Harwood, Aaron and Karunasekera, Shanika},
  title =	{{Introducing Diversion Graph for Real-Time Spatial Data Analysis with Location Based Social Networks}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{7:1--7:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.7},
  URN =		{urn:nbn:de:0030-drops-130428},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.7},
  annote =	{Keywords: moving objects, shortest path, graphs}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.9
Traffic Congestion Aware Route Assignment

Authors: Sadegh Motallebi, Hairuo Xie, Egemen Tanin, and Kotagiri Ramamohanarao

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract
Traffic congestion emerges when traffic load exceeds the available capacity of roads. It is challenging to prevent traffic congestion in current transportation systems where vehicles tend to follow the shortest/fastest path to their destinations without considering the potential congestions caused by the concentration of vehicles. With connected autonomous vehicles, the new generation of traffic management systems can optimize traffic by coordinating the routes of all vehicles. As the connected autonomous vehicles can adhere to the routes assigned to them, the traffic management system can predict the change of traffic flow with a high level of accuracy. Based on the accurate traffic prediction and traffic congestion models, routes can be allocated in such a way that helps mitigating traffic congestions effectively. In this regard, we propose a new route assignment algorithm for the era of connected autonomous vehicles. Results show that our algorithm outperforms several baseline methods for traffic congestion mitigation.
Cite as

Sadegh Motallebi, Hairuo Xie, Egemen Tanin, and Kotagiri Ramamohanarao. Traffic Congestion Aware Route Assignment. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{motallebi_et_al:LIPIcs.GIScience.2021.I.9,
  author =	{Motallebi, Sadegh and Xie, Hairuo and Tanin, Egemen and Ramamohanarao, Kotagiri},
  title =	{{Traffic Congestion Aware Route Assignment}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{9:1--9:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.9},
  URN =		{urn:nbn:de:0030-drops-130443},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.9},
  annote =	{Keywords: Road Network, Traffic Congestion, Route Assignment, Shortest Path}
}
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