Center for Sustainable Transportation Infrastructure Use of Probe Vehicles to Measure Road Ride Quality Samer W. Katicha Senior Research Associate, Center

Center for Sustainable Transportation Infrastructure

Use of Probe Vehicles to Measure Road Ride Quality

Samer W. KatichaSenior Research Associate,

Center for Sustainable transportation Infrastructure

Outline

o Smoothness for asset managemento Probe vehicleso The experiment

IRI calculation from profile

IRI calculation from vertical acceleration measurements

Sensitivity analysis

o Conclusions



Smoothness for asset managment

Infrastructure Condition/ Performance Indicators → Pavements

Service and User Perception

Physical Condition

Structural Integrity / Load-Carrying Capacity

Safety and Sufficiency

Environmental Impact

Serviceability (PSI, IRI)

Distress(PCI)

Deflection(FWD)

Friction (FN)/ Macrotexture

Tire/Pav. NoiseRolling Resistance

→ Pavements

Asset Management

o Strategic level Performance monitoring

o Network level Pavement management

o Project level Smoothness Specification Research LTPP


Project Level

Strategic Level

NetworkLevel

Performance

Structure Condition

Ride

Distress

Friction

IQL-5

IQL-4

IQL-3

IQL-2

IQL-1

System Performance

Monitoring

Planning andPerformance Evaluation

Program Analysis or

Detailed Planning

Project Level orDetailed Programming

Project Detail or

Research

HIGH LEVEL DATA

LOW LEVEL DATA

Business Processes

Info

rmat

ion

Qua

lity

Leve

ls

Information Quality Levels


Probe Vehicles

Can we use probe (or regular) vehicles for road infrastructure

health monitoring?

At least for supporting high-end strategic- and network-level decisions?

Pavement Assessment and Management Applications Enabled by the Connected Vehicles

Environment – Proof-of-Concept

Objective: To use data collected from probe vehicles to extract information that could be used to remotely and continuously determine road infrastructure health


The experiment

Profile and Acceleration Data

o Profile data: Collected at the Virginia Smart Road Every 30 mm (1.2 in)

o Probe vehicle acceleration data: Collected at the Virginia Smart Road Every 2100 mm (7 ft)


Data Sampling Problem


0 500 1000 1500 2000 2500-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Distance (mm)

Hyp

othe

tical

Pro

file

Smooth Profile Sampled at 150 mmRough Profile Sampled at 150 mmSmooth Profile Sampled at 2100 mmRough Profile Sampled at 2100 mm

Quarter Car Model


kt

kb Cb

Quarter Car Model


road

tire

tire

body

body

tire

tire

body

body

z

z

z

z

z

z

z

z

z

2211

11

0

0

0

1000

0010

kCkkCk

CkCk

body

b

M

kk 1

tire

t

M

kk 2

body

b

M

CC

body

tire

M

M

Accuracy of Numerical Calculation


0 500 1000 1500 2000 25000

1

2

3

4

IRI (

m/k

m)

0 500 1000 1500 2000 2500-0.01

-0.005

0

0.005

0.01

0.015

0.02

Distance (m)

Dif

fere

nce

IRI (

m/k

m)

IRI from ProfileIRI from Backcalculated Profile

The Probe Vehicle

o 2007 Ford Fusiono Car parameters:

Same as golden car Close enough

o Test Speed: 50 mph


IRI Calculation


0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

3.5

4

Distance (m)

IRI

(m/k

m)

Backcalculated IRI from probe vehiclebackcalculated IRI from profile calculated acceleration with 2 m samplingCalculated IRI

IRI Comparisons

o Calculated IRI: Follow the same trend Sample over 2 m makes a difference

o Problems with quarter car model: Probe vehicle acceleration results from

the full car response Approximate full car with average of

profile felt by the four wheels


“Full Car” IRI


0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

3.5

Distance (m)

MIR

I (m

/km

)

Probe Vehicle MIRIMIRI from Measured Profile: Average of all TiresMIRI from MEasured Profile: Average of Left and Right Wheel Path

Sensitivity Analysis (Sampling)


0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

3.5

Distance (m)

MIR

I (m

/km

)

Range of Profile Calculated MIRIProbe Vehicle Calculated MIRI

Sensitivity Analysis (Quarter Car Parameters)


Sensitivity Analysis (Sampling)


0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

0 500 1000 1500 2000 25000

0.5

1

1.5

2

2.5

3

Suspension Stiffness Suspension Damping

Tire Stiffness Mass Ratio

Conclusions

o Same IRI trend between probe vehicle and profiler: Effect of data sampling Effect of full vs. quarter car Effect of probe vehicle car parameters

o Use of the data: To much uncertainty/variation for

detailed analysis Maybe useful for strategic level


Blacksburg, VA

Documents

Center for Sustainable Transportation Infrastructure Use of Probe Vehicles to Measure Road Ride Quality Samer W. Katicha Senior Research Associate, Center