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Center for Sustainable Transportation Infrastructure
Use of Probe Vehicles to Measure Road Ride Quality
Samer W. KatichaSenior Research Associate,
Center for Sustainable transportation Infrastructure
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Outline
o Smoothness for asset managemento Probe vehicleso The experiment
IRI calculation from profile
IRI calculation from vertical acceleration measurements
Sensitivity analysis
o Conclusions
Center for Sustainable Transportation Infrastructure
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Center for Sustainable Transportation Infrastructure
Smoothness for asset managment
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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
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Asset Management
o Strategic level Performance monitoring
o Network level Pavement management
o Project level Smoothness Specification Research LTPP
Center for Sustainable Transportation Infrastructure
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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
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Center for Sustainable Transportation Infrastructure
Probe Vehicles
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Can we use probe (or regular) vehicles for road infrastructure
health monitoring?
At least for supporting high-end strategic- and network-level decisions?
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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
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Center for Sustainable Transportation Infrastructure
The experiment
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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)
Center for Sustainable Transportation Infrastructure
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Data Sampling Problem
Center for Sustainable Transportation Infrastructure
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
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Quarter Car Model
Center for Sustainable Transportation Infrastructure
kt
kb Cb
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Quarter Car Model
Center for Sustainable Transportation Infrastructure
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
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Accuracy of Numerical Calculation
Center for Sustainable Transportation Infrastructure
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
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The Probe Vehicle
o 2007 Ford Fusiono Car parameters:
Same as golden car Close enough
o Test Speed: 50 mph
Center for Sustainable Transportation Infrastructure
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IRI Calculation
Center for Sustainable Transportation Infrastructure
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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
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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
Center for Sustainable Transportation Infrastructure
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“Full Car” IRI
Center for Sustainable Transportation Infrastructure
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
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Sensitivity Analysis (Sampling)
Center for Sustainable Transportation Infrastructure
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
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Sensitivity Analysis (Quarter Car Parameters)
Center for Sustainable Transportation Infrastructure
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Sensitivity Analysis (Sampling)
Center for Sustainable Transportation Infrastructure
0 500 1000 1500 2000 25000
0.5
1
1.5
2
2.5
3
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0.5
1
1.5
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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
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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
Center for Sustainable Transportation Infrastructure
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Blacksburg, VA