Using Profile Data for Supporting Asset Management Decisions › media › files ›...
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Center for Sustainable Transportation Infrastructure
Using Profile Data for Supporting Asset Management Decisions
Gerardo W. FlintschDirector, Center for Sustainable transportation InfrastructureProfessor of Civil and Environmental Engineering
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Outline
o Asset Management decisionso How do we use profile data to support
these decisions?o What is the level of detail and accuracy
required?o Some potentially relevant questionso Final thoughts
Center for Sustainable Transportation Infrastructure
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Center for Sustainable Transportation Infrastructure
Asset Management decisions & business processes
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o Systematic process of maintaining, upgrading, and operating physical assets cost-effectively, efficiently, and comprehensively.
Engineering
Business-like
ObjectivesEconomics
Asset Management
Integration
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DATABASE
INV
ENTO
RY
CONDITION
USAGE
MAINTENANCESTRATEGIES
INFORMATION MANAGEMENT
NETWORK-LEVEL ANALYSISTOOLS
PROJECT LEVEL ANALYSIS (Design)
WORK PROGRAM EXECUTION
PERFORMANCEMONITORING
FEEDBACK
CONDITION ASSESSMENT
PRODUCTS
NETWORK-LEVEL REPORTS
Performance AssessmentNetwork NeedsFacility Life-cycle Cost Optimized M&R ProgramPerformance-based Budget
CONSTRUCTION DOCUMENTS
GRAPHICAL DISPLAYS
NEEDSANALYSIS
PRIORITIZATION / OPTIMIZATION
PERFORMANCE PREDICTION
PROGRAMMINGPROJECT SELECTION
Goals & PoliciesSystem PerformanceEconomic / Social &
Environmental
Budget Allocations
STRATEGIC ANALYSISThe Asset Management Process
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U.S. Map -21 National GoalsFocus the Federal-aid program on the following national goals:
1. Safety2. Infrastructure condition3. Congestion reduction4. System reliability5. Freight movement and economic vitality6. Environmental sustainability7. Reduced project delivery delays
Center for Sustainable Transportation InfrastructureSource: http://www.fhwa.dot.gov/policyinformation/presentations/
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DATABASE
INV
ENTO
RY
CONDITION
USAGE
MAINTENANCESTRATEGIES
INFORMATION MANAGEMENT
NETWORK-LEVEL ANALYSISTOOLS
PROJECT LEVEL ANALYSIS (Design)
WORK PROGRAM EXECUTION
PERFORMANCEMONITORING
FEEDBACK
CONDITION ASSESSMENT
PRODUCTS
NETWORK-LEVEL REPORTS
Performance AssessmentNetwork NeedsFacility Life-cycle Cost Optimized M&R ProgramPerformance-based Budget
CONSTRUCTION DOCUMENTS
GRAPHICAL DISPLAYS
NEEDSANALYSIS
PRIORITIZATION / OPTIMIZATION
PERFORMANCE PREDICTION
PROGRAMMINGPROJECT SELECTION
Goals & PoliciesSystem PerformanceEconomic / Social &
Environmental
Budget Allocations
STRATEGIC ANALYSISThe Asset Management Process
Goals & PoliciesSystem PerformanceEconomic / Social &
Environmental
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Center for Sustainable Transportation Infrastructure
How do we use profile data to support these decisions?
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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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Examples
o Strategic level Performance monitoring
o Network level Pavement management
o Project level Smoothness SpecificationResearch LTPP
Center for Sustainable Transportation Infrastructure
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Construction Acceptance
o Smoothness for quality acceptance Incentives for superior smoothnessDisincentives for roughness that
exceeds targets Virginia DOT: IRI “targets” for Interstate
and Non-Interstate pavements [applied to 0.01-mile (16 m) pay lots]
o Use of Ride Spec “turns back the clock” by as much as 7 years No significant impact on HMA bid price
(McGhee & Gillespie)Center for Sustainable Transportation Infrastructure
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Virginia Smoothness Specification
Center for Sustainable Transportation Infrastructure
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0 2 4 6 8 10 12 14 16 18 20
Time in Service (years)
IRI(
inch
es/m
ile)
w/o Spec Provw/ Spec Prov"Terminal" IRI
6 to 8 in/mi decrease
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Pavement Management
o Smoothness has been a key parameter for supporting network-level decisions since the genesis of PMSWhat, When, Where USA: AZ and KS started collecting roughness in
the early 70’s Developing counties: key input for the HDM model
o Trigger preservation & rehabilitatiotno Impact on user costs and environmental impacts
Center for Sustainable Transportation Infrastructure
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VA: Average IRI by County (1997)Primary Highways
Source: 1997 State of the Pavement Report
f1
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Bild 14
f1 start here Thflintsch; 2005-09-15
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0
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1972 1977 1982 1987 1992 1997 2002Year
Rou
ghne
ss (M
aysm
eter
Uni
ts)
`
RSL
I 10 WB, MP 337 - 344
Preservation Treatment
Threshold Roughness Value for Interstates
Roughness Prediction for AZ DOT
Effect of M&R
Remaining Service Life Estimate
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System Performance Monitoringo Federal government in the US has used
smoothness for assessing road performance for many years. FHWA (old) Roughness Objective: “To increase the
percentage of miles on the NHS that meet Owner-Agency managed pavement performance for acceptable ride quality to over 93 percent within 10 years”
IRI less than or equal to 170 inches/mileo Needs reliable data for aligning investments
with desired performance→ HPMS → HERS
Center for Sustainable Transportation Infrastructure
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Performance Measures Being Considered for MAP 21 (§150(c))
PROGRAM MEASURE CATEGORYNational Highway Performance Program
• Pavement Condition on the Interstates• Pavement Condition on Non-Int. NHS • Bridge Condition on NHS• Performance of Interstate System • Performance of Non-Interstate NHS
Highway Safety Improvement Program
• Serious Injuries per VMT• Fatalities per VMT• Number of Serious Injuries• Number of Fatalities
CMAQ Program • Traffic Congestion• On-road mobile source emissions
Freight Policy • Freight Movement on the Interstate
Source: T. Van, 11th Infrastruture Management Research and Education Workshop, Washington, DC, Jan 2013
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Condition of Principal Highways (2009)
Source: http://www.fhwa.dot.gov/policyinformation/pubs/hf/pl11028/chapter7.cfm
Highway Fatality RatesInterstate Pavement Smoothness (IRI) by State
Bridge Deficiencies
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Center for Sustainable Transportation Infrastructure
What is the level of detail and accuracy required?
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1. Organize annual equipment “rodeos” + verification
2. Seasonal monitoring
3. Evaluation & development of new technologies
4. Evaluation of high-friction systems
5. CFME deployment &friction technology transfer
6. Outreach: Pavement Evaluation 2010SURF 2012
Background: Pavement Surface Properties Consortium
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Equipment Comparisons / “Rodeos”o Since 2007o Profile, friction, textureo Added Noiseo AASHTO R56 for
certification
Center for Sustainable Transportation Infrastructure
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AASHTO R56
o Focused on profilers used for quality control and also applicable for network profilers
o Uses cross correlation to evaluate: Repeatability (CC ≥ 92%)
Ten runs Cross correlate with each other and average
Accuracy (CC w/ reference ≥ 90%) Ten runs Cross correlate with reference and average
ProVAL SoftwareCenter for Sustainable Transportation Infrastructure
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“Rodeo” concept closely tied to US RPUG
Center for Sustainable Transportation Infrastructure
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We run ours at the Virginia Smart Road
VTTI
Bridge
Road
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Reference Profiler Comparison
Cross-Correlation
Left Right
SECTION 1 JRCP 92.1 94.1
SECTION 2 CRCP G&G 72.8 66.6
SECTION 3 SMA/OGFC 91.7 92
SECTION 4 SM 9.5 91.9 90.2
SECTION 5 SM 9.5/12.5 89.7 92.8
Can we use it smooth pavements?
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IRI Comparison – Section 4 SM 9.5
2012
2013
99 10098 10293
9894 9790
10195 9894
10393
98
0
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120
LWP RWP
IRI (
in/m
i)
1019698 9696 9593
10096 98101 989994
10196
100 9798 94
0
20
40
60
80
100
120
LWP RWP
IRI (
in/m
i)
Reference
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Repeatability – Section 4 SM 9.5
95 93 93 93 91 9095 94 94 94
97 9794
9197
929491 93 94 93 94 94 93
95 9397 95 94
9196
94
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Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right
GA MS SC1 SC2 AMES VTTI VA PENN
%
25 mph 45 mphAverage Left: 93.7 % Average Right: 93.9 %
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Reproducibility – Section 4 SM 9.576 75
83 8374 72 67 63
91 9095 93
70 68
88 8879 76
84 8069 67 68 64
90 87 89 87
7166
89 87
0102030405060708090
100
Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right
GA MS SC1 SC2 AMES VTTI VA PENN
%45 mph
Surpro VT Surpro MSAverage Left: 79.6 % Average Right: 78.4 %
73 7482 82
75 73 73 70
92 90 94 90
68 67
89 88
75 7482 78
71 6977
72
91 88 85 8170
65
89 86
0102030405060708090
100
Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right
GA MS SC1 SC2 AMES VTTI VA PENN
%
25 mph
Surpro VT Surpro MSAverage Left: 80.0% Average Right: 78.3%
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Center for Sustainable Transportation Infrastructure
Some potentially relevant questions
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Do we need a “hierarchical” specification for profilers?
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Project Level
Strategic Level
NetworkLevel
Performance
Structure Condition
IQL-5
IQL-4
IQL-3
IQL-2
IQL-1
SystemPerformanceMonitoring
Planning andPerformance Evaluation
Program Analysis orDetailed Planning
Project Level orDetailed Programming
Project Detail orResearch
HIGH LEVEL DATA
LOW LEVEL DATA
Information Quality Levels
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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 determineroad infrastructure health
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Comparison
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Is IRI the most appropriate way of summarizing the profile data?
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How significant is the impact of smoothness on vehicle operation
costs and GHG emissions?
Center for Sustainable Transportation Infrastructure
Can profile data help more “sustainable” network-level pavement management decisions?
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1.21.41.61.822.22.42.62.83
x 107
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Condition
Energy Consumption (MJ)
Cos
t (Te
ns o
f Tho
usan
ds o
f Dol
lars
)
50th Percentile5th Percentile95th Percentile
Incorporating pavement LCA use-phase into pavement management
MinMax
Min
MinMax
Max
MinMax
MinCostCost
CostCost,
ConditionConditionConditionCondition
,EnergyEnergy
EnergyEnergy
Nat
iona
l Sus
tain
able
Pav
emen
t Con
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ium
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Center for Sustainable Transportation Infrastructure
Final Thoughts
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Final Thoughts
o Profile data is a key asset management input→ user perception & level of service
o It is used (and needed) for supporting business processes at various management levels
o We may not need the same degree of detail and accuracy for all levels
Center for Sustainable Transportation Infrastructure
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Blacksburg, VA