CSA’s Growing Pains Analysis by Steve Bryan [email protected].

CSA’s Growing Pains

Analysis by Steve [email protected]

Crash Accountability

Analysis by Steve [email protected]

DOT Reportable

State Disparity – Enforcement

Analysis by Steve [email protected]

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6

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7

About Tableau maps: www.tableausoftware.com/mapdata

11.55

12.55

10.25

15.25

15.2810.79

19.7810.49

15.38 12.19

17.5915.58

13.38

47.06

11.04

13.70

14.50

30.52 11.81

11.3110.41

7.45

2.65

7.792.88 4.59

8.67

6.57

9.94

9.44

4.72

5.72

6.22

7.81

7.01

8.11

MD25.80

Vehicle Maintenance Inspections/MCVMT

WY40.4

WV39.5

WI38.6

WA51.4

VT42.0

VA49.9

UT

TX175.4

TN

SD46.5

SC40.9

PA24.6

OR35.7

OK

OH39.2

NY57.6

NV52.4

NM37.0

NJ25.1

NH56.5

NE39.6

ND

NC28.7

MT72.1

MS30.6

MO57.7

MN55.6

MI30.8

ME48.4

MD90.9

MA24.7

LA37.7

KY52.6

KS58.6

IN

IL16.9

ID28.4

IA71.5

GA26.7

FL24.4

DE

CT88.4

CO39.0

CA57.2

AZ105.3

AR30.5

AL

Based on 2011 FHWA data. District of Columbia and Rhode Island have low Commercial Vehicle Miles and were removed from this view.

Vehicle Maintenance CSA Points/MCVMT

2.65 47.06VM Inspections/MCVMT

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8

WY0.88

WV0.47

WI0.54

WA0.37

VT1.63

VA0.63

UT0.51

TX1.46

TN

SD0.51

SC0.66

PA

OR0.49

OH0.73

NY2.01

NV1.10

NM

NJ0.80

NH0.99

NE0.90

ND0.22

NC

MT0.79

MS0.21

MO0.33

MN1.96

MI0.51

ME0.70

MD0.77

MA2.29

LA0.46

KY

KS0.82

IN

IL0.48

ID0.89

IA1.49

GA0.63

FL0.53

CT0.96 CO

0.72

CA0.34

AZ1.03

AR

Based on 2011 FHWA data. District of Columbia and Rhode Island have low Commercial Vehicle Miles and were removed from this view.

Hazmat CSA Points/MCVMT

About Tableau maps: www.tableausoftware.com/mapdata

0.05

0.15

0.05

0.05

0.15

0.150.15

0.15

0.09

0.09

0.08

0.17

0.06

0.07

0.260.17

0.07

0.13

0.27

0.17 0.07

0.06

0.33

0.03

0.33

0.20

0.040.14

0.10

0.04

0.10

0.10

0.20

0.12

0.22

0.11 0.11MA0.37

Hazmat Inspections/MCVMT

0.02 0.37Hazmat Inspections/MCVMT

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9

Regional Enforcement DisparityExample – Traffic Enforcement vs Roadside

Light:Speed™ Ratio – 28.36 (Florida)

Light:Speed™ Ratio – 12.17 (South Carolina)

Light:Speed™ Ratio – 40.40 (Louisiana)

Light:Speed™ Ratio – 1.91 (Indiana)

Light:Speed™ Ratio – 11.97 (US)

Light:Speed™ Ratio – 321.02 (Texas)

Analysis by Steve [email protected]

You can’t “fix” disparate enforcement…

Safety Event Groups

Analysis by Steve [email protected]

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 BASICs

242,199 carriers across 29 safety event groups15 Safety Event Groups are not represented (private) because FMCSA does not make them available in the SMS preview.

Drug & Alc.

Driver Fitness

HOS Compliance

Unsafe - Straight

Unsafe - Combo

Maintenance

Linear Trend Model

Two extreme outliers, one from each data set, removed due to outrageously erroneous data

Crashes/MMCrashes/PU

Linear

4th Degree Polynomial Trend Model

Two extreme outliers, one from each data set, removed due to outrageously erroneous data

4th Degree Polynomial

Linear

Poly 4

Poly 4

Poly 4

Poly 4

…

1. Measure to Percentile relationship is consistently skewed across all BASICs2. Using Power Units as the basis for crash rate makes little sense3. A linear trend model is not appropriate on the surface, nor is it borne out as useful when applied4. 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 behavior6. When regression analysis is applied to Percentiles:Crashes/MM, there is still no meaningful predictive value (R2 never gets beyond approx .3)