Fast Vision-Based Road Tunnel Detection

  • Massimo Bertozzi
  • Alberto Broggi
  • Gionata Boccalini
  • Luca Mazzei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6979)

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 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Broggi, A., Mazzei, L., Porta, P.P.: Car-driver cooperation in future vehicles. In: Procs. Intl. Conf. on Models and Technologies for Intelligent Transportation Systems, Rome, Italy (June 2009)Google Scholar
  2. 2.
    Daytime Running Lights Deliverable 3: Final Report (October 2003)Google Scholar
  3. 3.
    D.M. 5 giugno,”Sicurezza nelle gallerie stradali”. Pubblicato nella Gazzetta Ufficiale (217) (Settembre 18, 2001)Google Scholar
  4. 4.
    Ziemer, R.E., Peterson, R.W.: Introduction To Digital Communication, 2nd edn. Prentice-Hall, Englewood Cliffs (2000)Google Scholar
  5. 5.
    Cabani, I., Toulminet, G., Bensrhair, A.: Contrast-invariant Obstacle Detection System using Color Stereo Vision. In: 11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008, Beijing (October 2008)Google Scholar

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

Personalised recommendations