Determining the minimal safety level of automatic road sign recognition system – field study survey

In this paper, the authors investigated human drivers’ road sign recognition capability to determine the minimum safety level demanded from artificial intelligence. Therefore, the authors build up a survey and tested drivers to determine the meaning of roadside signs. A small sample was required as a pilot project with 51 respondents. Most of them were male and young. As preliminary result authors have found that the roadside human recognition has been significantly influenced by the age, the year of obtaining the license, and the driver practice.

• Record URL:
  https://doi.org/10.1016/j.trpro.2021.06.035
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2352146521003835
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2021 Henrietta Lengyel, et al. Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Lengyel, Henrietta
  • Valoczi, Denes
  • Torok, Adam
• Conference:
  • 14th International Scientific Conference on Sustainable, Modern and Safe Transport (TRANSCOM)
  • Date: 2021-5-26 to 2021-5-28
• Publication Date: 2021

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 307-312
• Serial:
  • Transportation Research Procedia
  • Volume: 55
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Age; Artificial intelligence; Character recognition; Statistical analysis; Traffic signs; Vision
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01781071
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 31 2021 4:50PM