• DocumentCode
    2634318
  • Title

    RAMS Analysis of a Bio-inspired Traffic Data Sensor ("Smart Eye")

  • Author

    Bohm, P. ; Gruber, Thomas

  • Author_Institution
    Dept. Safety & Security, Austrian Res. Centers GmbH-ARC, Vienna, Austria
  • fYear
    2009
  • fDate
    27-29 Aug. 2009
  • Firstpage
    546
  • Lastpage
    552
  • Abstract
    The Austrian Research Centers have developed a compact low-power embedded vision system "Smart Eye TDS", capable of detecting, counting and measuring the velocity of passing vehicles simultaneously on up to four lanes of a motorway. The system is based on an entirely new bio-inspired wide dynamic ¿silicon retina¿ optical sensor. Each of the 128 × 128 pixels operates autonomously and delivers asynchronous events representing relative changes in illumination with low latency, high temporal resolution and independence of scene illumination. The resulting data rate is significantly lower and reaction significantly faster than for conventional vision systems. In ADOSE, an FP7 project started 2008 (see acknowledgment at the end of the paper), the sensor will be tested on-board for pre-crash warning and pedestrian protection systems. For safety-related control applications, it is evident that dependability issues are important. Therefore a RAMS analysis was performed with the goal of improving the quality of this new traffic data sensor technology, in particular with respect to reliability and availability. This paper describes the methods used and the results found by applying a RAMS analysis to this specific case of a vision system.
  • Keywords
    computer vision; embedded systems; image resolution; image sensors; intelligent sensors; optical sensors; road safety; road traffic; road vehicles; traffic engineering computing; velocity measurement; RAMS analysis; Smart Eye TDS; bioinspired traffic data sensor; compact low-power embedded vision system; image resolution; motorway; passing vehicle; pedestrian protection system; precrash warning; safety-related control application; scene illumination; silicon retina optical sensor; velocity detection; velocity measurement; Biosensors; Intelligent sensors; Intelligent vehicles; Lighting; Machine vision; Optical sensors; Remotely operated vehicles; Vehicle detection; Vehicle dynamics; Velocity measurement; FMEA; RAMS; bio-inspired sensor; harsh environment; reliability analysis; silicon retina; traffic data sensor; vision system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Advanced Applications, 2009. SEAA '09. 35th Euromicro Conference on
  • Conference_Location
    Patras
  • ISSN
    1089-6503
  • Print_ISBN
    978-0-7695-3784-9
  • Type

    conf

  • DOI
    10.1109/SEAA.2009.71
  • Filename
    5350013