Fast Vision-Based Road Tunnel Detection

  • Massimo Bertozzi
  • Alberto Broggi
  • Gionata Boccalini
  • Luca Mazzei
Conference paper

DOI: 10.1007/978-3-642-24088-1_44

Volume 6979 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Bertozzi M., Broggi A., Boccalini G., Mazzei L. (2011) Fast Vision-Based Road Tunnel Detection. In: Maino G., Foresti G.L. (eds) Image Analysis and Processing – ICIAP 2011. ICIAP 2011. Lecture Notes in Computer Science, vol 6979. Springer, Berlin, Heidelberg

Abstract

When a vehicle equipped with an artificial vision system enters or exits a tunnel, the camera may temporarly suffer from reduced visibility, or even get completely blind due to quick changes in enviromental illumination.

This paper presents a vision-based system that detects approaching tunnels entrances or exits. The proposed system allows other ADAS (Advanced Driver Assistance Systems) to act on camera parameters to effectively avoid the tunnel blindness effect. Information regarding approaching tunnel entrance can be helpful for other sensors as well and for sensor fusion systems. In terms of path planning, this system can also inform GNSS-based systems (Global Navigation Satellite System), which usually do not receive any signal in tunnels, and trigger dead reckoning techniques.

The proposed system is noticeably fast and therefore well fit to be used as a background process to support other ADAS applications.

Keywords

Intelligent vehicle autonomous driving ADAS tunnel detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Massimo Bertozzi
    • 1
  • Alberto Broggi
    • 1
  • Gionata Boccalini
    • 1
  • Luca Mazzei
    • 1
  1. 1.VisLab - Dipartimento di Ingegneria dell’InformazioneUniversità degli Studi di ParmaItaly