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CSA’s Growing Pains

CSA’s Growing Pains. Analysis by Steve Bryan s.bryan@vigillo.com. Crash Accountability. Analysis by Steve Bryan s.bryan@vigillo.com. DOT Reportable. State Disparity – Enforcement . Analysis by Steve Bryan s.bryan@vigillo.com. RETURN. RETURN. RETURN. RETURN.

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CSA’s Growing Pains

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  1. CSA’s Growing Pains Analysis by Steve Bryan s.bryan@vigillo.com

  2. Crash Accountability Analysis by Steve Bryan s.bryan@vigillo.com

  3. DOT Reportable

  4. State Disparity – Enforcement Analysis by Steve Bryan s.bryan@vigillo.com

  5. RETURN

  6. RETURN

  7. RETURN

  8. RETURN

  9. Regional Enforcement Disparity Example – Traffic Enforcement vs Roadside Light:Speed™ Ratio – 11.97(US) Light:Speed™ Ratio – 12.17(South Carolina) Light:Speed™ Ratio – 28.36(Florida) Light:Speed™ Ratio – 40.40 (Louisiana) Light:Speed™ Ratio – 1.91(Indiana) Light:Speed™ Ratio – 321.02 (Texas)

  10. You can’t “fix” disparate enforcement… Analysis by Steve Bryan s.bryan@vigillo.com

  11. Safety Event Groups Analysis by Steve Bryan s.bryan@vigillo.com

  12. The following slides are the result of my first look at the make-up of the 29 Safety Event Groups based on the Public CSA BASICs242,199 carriers across 29 safety event groups15 Safety Event Groups are not represented (private) because FMCSA does not make them available in the SMS preview.

  13. Drug & Alc.

  14. Driver Fitness

  15. HOS Compliance

  16. Unsafe - Straight

  17. Unsafe - Combo

  18. Maintenance

  19. Linear Trend Model Crashes/MM Crashes/PU Two extreme outliers, one from each data set, removed due to outrageously erroneous data

  20. Linear

  21. 4th Degree Polynomial Trend Model Two extreme outliers, one from each data set, removed due to outrageously erroneous data

  22. 4th Degree Polynomial

  23. Linear

  24. Poly 4

  25. Poly 4

  26. Poly 4

  27. Poly 4

  28. … 1. Measure to Percentile relationship is consistently skewed across all BASICs 2. Using Power Units as the basis for crash rate makes little sense 3. A linear trend model is not appropriate on the surface, nor is it borne out as useful when applied 4. A 4th order polynomial regression trend model fits the data better, but still does not result in meaningful predictive value (low R2) 5. Crashes/MM is a better measure of activity and presumably controllable behavior 6. When regression analysis is applied to Percentiles:Crashes/MM, there is still no meaningful predictive value (R2 never gets beyond approx .3)

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