Towards a reliable speed-limit assistant combining Traffic Sign Recognition with GPS information

Abstract : Being able to always know the current speed-limit is a highly interesting feature both for driver information system, and for advanced driving assistance such as a smart Adaptive Cruise Control (ACC) automatically adapting vehicle speed to current speed-limit. However, this kind of function can be really valuable and of practical use only if the produced speed-limit information is extremely reliable. Using vision-based Traffic Sign Recognition alone cannot be robust enough, as there will always be cases in which some sign is missed because of occlusion by another vehicle. Conversely, the system cannot rely only on cartographic navigation information, because it has to take into account roadwork temporary limits as well as variable speed limits enforced by LED signs, and also supplementary signs located below main signs and modifying their scope (class of vehicle, concerned lane, etc...), which requires quite robust vision-based recognition of several kinds of traffic-signs. Even proprioceptive information such as current speed, turn indicators, steering wheel angle (, etc...) could be necessary for a correct system. In this paper, we present several of the required bricks for building such a reliable speed-limit support system: a performant recognition of speed-limit-signs working on various European roads (despite sign variability between country) and able to operate correctly also on LED signs and at night, good detection of end-of-speed-limit-signs, a method for effective detection and recognition of supplementary signs, and a general framework for intelligent fusion, using Belief Theory, of information deduced from vision and navigation. All these functions are implemented modularly, and have been evaluated both on real recorded videos, and by on-road real-time tests.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00435682
Contributor : Fabien Moutarde <>
Submitted on : Tuesday, November 24, 2009 - 3:55:32 PM
Last modification on : Wednesday, February 6, 2019 - 10:18:07 AM

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  • HAL Id : hal-00435682, version 1

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Alexandre Bargeton, Fabien Moutarde, Fawzi Nashashibi, Benazouz Bradai, Lowik Chanussot. Towards a reliable speed-limit assistant combining Traffic Sign Recognition with GPS information. British Machine Vision Association (BMVA) technical meeting on "Vision for Automotive Applications", May 2009, London, United Kingdom. ⟨hal-00435682⟩

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