Possible uses of data from the HU-GO electronic toll system for an automatic incident detection algorithm

  • Mánuel Gressai Budapesti Műszaki és Gazdaságtudományi Egyetem Közlekedésmérnöki és Járműmérnöki Kar
  • Róbert Péter Tóth Budapesti Műszaki és Gazdaságtudományi Egyetem Közlekedésmérnöki és Járműmérnöki Kar
  • Tamás Dr. Tettamanti Budapesti Műszaki és Gazdaságtudományi Egyetem Közlekedésmérnöki és Járműmérnöki Kar
Keywords: road traffic, incident, detection algorithm

Abstract

The basic task of the National Toll Payment Services PLC (NÚSZ) is to sell road use authorization and to verify the existence of such autorizations and to provide related services. Traffic monitoring on the toll road network is carried out by means of nearly 130 fixed toll gates equipped with cameras and laser scanners, and video equipment mounted on vehicles. A large amount of detailed data is generated during the verification of the right to use the road, which can be used for traffic management and automatic incident detection (AID) algorithms. In this paper, the different AID methods are described, followed by the tuning methodology of the ARIMA model-based algorithm and the examination of the effectiveness of different versions tested with real data.

References

Horváth, M.T., 2012. Automatikus incidensfelismerő algoritmusok összehasonlítás autópályán, BSc szakdolgozat

Martin, P.T., Perrin, J., Hansen, B., Kump, R. and Moore, D., 2001. Incident detection algorithm evaluation. Prepared for Utah Department of Transportation.

Parkany, E. and Xie, C., 2005. A complete review of incident detection algorithms & their deployment: what works and what doesn't.

Mahmassain, H.S., Haas, C., Zhou, S. and Peterman, J., 1999. Evaluation of incident detection methodologies (No. FHWA/TX-00/1795-1). University of Texas at Austin. Center for Transportation Research.

Published
2022-12-15
How to Cite
GressaiM., TóthR. P., & Dr. TettamantiT. (2022). Possible uses of data from the HU-GO electronic toll system for an automatic incident detection algorithm. Scientific Review of Transport, 72(6), 17-25. https://doi.org/10.24228/KTSZ.2022.6.2
Section
Articles