30 years on the Road To Progressively Better Data

Pavement Friction Management (PFM) Support Program

Lessons Learned – First draftBy

Edgar David de Leon Izeppi, Research Scientist *

Virginia Tech Transportation Institute

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Presentation Outline

• Introduction

• Case Studies of Continuous Measurements (Examples)• Friction

• Texture

• Geometrics and all of the above

• Crash cost analysis and comparisons

• Conclusions

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Introduction

IF you had all the money of the world, what car would you buy?

Stay tuned…

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

•1: Macrotexture

•2: Microtexture

•3: Dry Contact

THREE ZONE CONCEPT

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Importance of Continuous Measurements

•CFME and texture data collection

Geometrics and all of the above

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

2 for 8

30 years on the Road To Progressively Better Data14

SR30 Friction Color Codes1. SR30 > 502. SR30 45-503. SR30 40-454. SR30 < 40

30 years on the Road To Progressively Better Data15

SR30 Friction Color Codes1. SR30 > 502. SR30 45-503. SR30 40-454. SR30 < 40

30 years on the Road To Progressively Better Data

-7.8

-8.0

-7.2

-7.2

-7.7

-7.8

-7.7

-7.5

-8.2

-8.5

-7.5

-7.1

-7.0

-6.9

-6.6

-6.6

-6.8

-6.1

-5.9

-245

-196

-171

-185

-187

-204

-190

-167

-177

-194

-193

-182

-163

-174

-184

-177

-186

-210

-231

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Importance of Continuous Measurements

•Comparison CFME and texture data collection with 1.0 mile Friction

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Pavement Conditions Vary

•NCHRP Report 37, 1967: • “Because the intensity of the polishing process

increases markedly with tread element slip, all other factors being equal, the lowest friction levels are found on high-speed roads, curves, and approaches to intersections; in short, in locations at which high friction values are needed most.”

18

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

State Route A (MM 59.8)

“Because the

intensity of the

polishing process

increases markedly

with tread element

slip, all other factors

being equal, the

lowest friction levels

are found on high-

speed roads,

curves, and

approaches to

intersections; in

short, in locations at

which high friction

values are needed

most.”NCHRP Report 37, 1967

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

1. Good SR > 502. Fair SR 45-503. Poor SR 40-454. Very Poor SR < 40

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

FRICTION initial results

Friction DemandCategory

SR30 Threshold Other (Speed)

Non-events divided 30 – 35 35 – 40

Non-events undivided 35 – 40

Curves (R < 2,000’) 40 – 45

Intersections 45 – 50 40 – 45

Grade > 5% TBD

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Importance of Continuous Measurements

•CFME and texture data collection

Texture

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better DataAdvancing Transportation Through Innovation

30 years on the Road To Progressively Better Data

Preliminary Crash Data

24

39% to 66%

21% to 23%

28% to 50%

21% to 28%

30 years on the Road To Progressively Better Data

Preliminary Crash Data

25

Route Summary

• Section 3, 4, and 6 – 55 MPH

– 9.09 Miles (years before – 3.00, years after – 1.21) ADT = 15,000-18,000

– Total Crashes before = 119 after = 72

– Wet Crashes before = 33 (28%) after = 21 (29%)

– Wet/Year/Mile before = 1.21 after = 1.91 (58% +)

– S9.5C (2015) SR 30 = 51.3-57.1 MPD = 0.37-0.40

• Section 2 and 7 – 70 MPH

– 24.10 Miles (years before – 3.00, years after – 1.21) ADT = 15,000-18,000

– Total Crashes before = 269 after = 234

– Wet Crashes before = 112 (42%) after = 157 (67%)

– Wet/Year/Mile before = 1.55 after = 5.38 (248% +)

– S9.5C (2015) SR 30 = 60.4-60.5 MPD = 0.38-0.40https://connect.ncdot.gov/projects/research/Pages/ProjDetails.aspx?ProjectID=2017-02

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

TEXTURE initial results (mm)

Speed Limits (mph) SR 30 > 0.40 SR30 < 0.40

< 35 0.5 0.6

35 – 50 0.6 0.7

50 – 70 0.7 0.8

> 70 0.8 1.0

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Crash Cost Considerations

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Crash Costs vs. Treatments

Crash Category Virginia Crashes 1

Category % Cost ($1,000) 2 Total Cost ($1,000)

PDO 77,941 63.1% $6.1 $473,570

Injury 44,924 36.4% $167.5 $7,525,803

Fatality 714 0.6% $9,146.0 $6,530,243

Total 123,579 $14,529,615

Notes:1. Year 2,0102. NHTSA Cost Report, 2,010 Average cost:

$117,573

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Crash Costs vs. Treatments

FrictionTreatment

TreatmentCost 2

Treatment costper one-crash

Treatments of0.1-mile sectionsper one-crash

CR per $0.5million of savingsper 0.1-milesection

DGAC O/L $15,000 0.10 9.7 3.5

OGFC 1 $22,500 0.15 6.5 3.6

CDG $7,000 0.05 20.8 3.5

HFS $40,000 0.27 3.6 3.7Notes:1. 1.5 cost of DGAC (18/12)2. For 0.1-mile, 12 foot-lane

30 years on the Road To Progressively Better Data30 years on the Road To Progressively Better Data

Conclusions

Hurdles to overcome:

1. INMP syndrome (full cooperation with Safety)

2. Financial vs. Economic Considerations

3. Act today, commit, and do ita. Special Task Forceb. Interdivision Cooperationc. Consider other ideas

30 years on the Road To Progressively Better Data

Montana

30 years on the Road To Progressively Better Data

Since 1953, +20,000markershttps://billingsgazette.com/news/state-and-regional/montana/memorial-markers-for-years-white-crosses-have-marked-fatal-accidents/article_6c23cb4a-af89-5347-8df1-51b652946453.html

30 years on the Road To Progressively Better Data

https://billingsgazette.com/news/state-and-regional/montana/memorial-markers-for-years-white-crosses-have-marked-fatal-accidents/article_6c23cb4a-af89-5347-8df1-51b652946453.html

30 years on the Road To Progressively Better Data

PAVEMENT EVALUATION 2019

Roanoke, VA

September 17-21, 2019

Sept.

17-21

2019

30 years on the Road To Progressively Better Data

http://saferroadsconference.com

Advancing Transportation

Through Innovation

May 14 – 16, 2020

Greater Richmond Convention Center

Host Hotel –Marriot Richmond

30 years on the Road To Progressively Better Data

Answer

30 years on the Road To Progressively Better Data

Duncan Imports & Classic Cars

“Christiansburg car collection catching the eye of Bill Gates, NASCAR drivers and movie studios”, Roanoke Times 9/4/18 https://www.roanoke.com/news/local/christiansburg/christiansburg-car-collection-catching-the-eye-of-bill-gates-nascar/article_e1f9f35a-0d33-5be0-b0d7-0235840563b1.html

What is the purpose to get the car? “900 cars and counting: How one man's secret collection drew international fame”, by Jacob Demmitt, Roanoke Times, 7/29/17 https://www.roanoke.com/townnews/motor_vehicle/cars-and-counting-how-one-man-s-secret-collection-drew/article_cc20c7fa-73a3-11e7-a460-af9d1cae7d48.html

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data

What are these two in the right?

30 years on the Road To Progressively Better Data

30 years on the Road To Progressively Better Data