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Documents authored by Jongwiriyanurak, Natchapon

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.44
Framework for Motorcycle Risk Assessment Using Onboard Panoramic Camera (Short Paper)

Authors: Natchapon Jongwiriyanurak, Zichao Zeng, Meihui Wang, James Haworth, Garavig Tanaksaranond, and Jan Boehm

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

Abstract
Traditional safety analysis methods based on historical crash data and simulation models have limitations in capturing real-world driving scenarios. In this experiment, panoramic videos recorded from a motorcyclist’s helmet in Bangkok, Thailand, were narrated using an image-to-text model and then put into a Large Language Model (LLM) to identify potential hazards and assess crash risks. The framework can assess static and moving objects with the potential for early warning and incident analysis. However, the limitations of the existing image-to-text model cause its inability to handle panoramic images effectively.
Cite as

Natchapon Jongwiriyanurak, Zichao Zeng, Meihui Wang, James Haworth, Garavig Tanaksaranond, and Jan Boehm. Framework for Motorcycle Risk Assessment Using Onboard Panoramic Camera (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 44:1-44:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{jongwiriyanurak_et_al:LIPIcs.GIScience.2023.44,
  author =	{Jongwiriyanurak, Natchapon and Zeng, Zichao and Wang, Meihui and Haworth, James and Tanaksaranond, Garavig and Boehm, Jan},
  title =	{{Framework for Motorcycle Risk Assessment Using Onboard Panoramic Camera}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{44:1--44:7},
  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.2023.44},
  URN =		{urn:nbn:de:0030-drops-189394},
  doi =		{10.4230/LIPIcs.GIScience.2023.44},
  annote =	{Keywords: Traffic incident risk, Large Language Model, Vision-Language Model}
}
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