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Lauren Zelinski ENGR 518 December 4 th ,2012

Lauren Zelinski ENGR 518 December 4 th ,2012. Purpose. Predicting traffic flow rates Measuring traffic density Increasing safety Enforcing traffic laws in intersections. Full setup of the intersection Wireless detection sensor Camera Video Strobe images. Length of Green Signal

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Lauren Zelinski ENGR 518 December 4 th ,2012

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  1. Lauren ZelinskiENGR 518December 4th,2012

  2. Purpose • Predicting traffic flow rates • Measuring traffic density • Increasing safety • Enforcing traffic laws in intersections

  3. Full setup of the intersection • Wireless detection sensor • Camera • Video • Strobe • images

  4. Length of Green Signal Te-min=max(n*ts L/V) N=number vehicle ts=mean time headway in saturated traffic flow V= mean speed

  5. Traffic density vs speed q=kv v=mean speed q=traffic flow rate k=traffic density

  6. Traffic flow rate vs density V=vf(1-k/kj)

  7. Image verification and clarity Process digital image information by selectively modifying pixel intensity information in order to improve legibility or visibility of parts of a digital image. How red light runners are caught and license plate numbers processed

  8. Higher intensities around the license plate and headlights are made clearer as this 8-bit image is processed to a 4-bit image

  9. Algorithm for mapping 8-bit pixel intensity information to 4-bit focusing on higher intensity areas Histogram of intensity of pixels in speed violation image

  10. Dynamic range of Camera When processing digital images the camera needs to have a sufficient "dynamic range" to resolve all the light intensities under consideration. The dynamic range of a CCD (Charge-coupled device) imaging system 30 is the ratio of CCD saturation (full well charge) to the read noise The dynamic range is 45,000/11= 354091 levels or 20 Log 10(4091)=71 dB. This produces a large volume of data. A 12 bit ADC produces 4096 levels, which in the case of an RGB CCD translates to 6.9x1010 bits of RGB information which are beyond the resolving capabilities of the human eye. The average human eye can only resolve 64 or at most 128 grey levels or intensities.

  11. Charge coupled device collects image and breaks into Red Green Blue analog streams which are then passed through an analog to digital converter Passed to digital signal processor and filters 16-bit into 8-bit using intensity criteria described earlier and then converted to compact YUV and final the data compression algorithm is applied

  12. 4-bit version of earlier image after processes according to the algorithm The higher intensity pixels around plate are now easier to read

  13. References • Andreassen D. (1995) A long term study of red light cameras and accidents, Report ARR 261, Australian Road Research Board, Vermont. • Moran, M.A., Engelman, L., Fitzgerald, G., & Lynch, B. (1993) Polychotomousstepwise logistic regression. In BMDP Manual, Version 7 • US patent 5444442 sadakata et al. • US patent 6240217 B1 Ercan et al.

  14. Questions???

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