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Center for Risk Management of Engineering Systems University of Virginia, Charlottesville

Slide 1

MANAGING THE MAINTENANCE OF VIRGINIA’S ROADS AND HIGHWAYS

Progress Report

Presented toProject Steering Committee

By

Center for Risk Management of Engineering SystemsUniversity of Virginia

March 20, 2002


Slide 2

Team MembersCenter for Risk Management

of Engineering Systems:• Yacov Haimes• James Lambert• Barry Horowitz• Michael Pennock• Ruth Dicdican• Satish Kartha• John Robinson • Justin Rousseau• Alex Uhl• Chad Warner

Virginia Transportation Research Council:

• William Bushman• Wayne Ferguson• Jose Gomez• Robert Hanson• Dan Roosevelt (leading adviser)

VDOT:• Steve Mondul


Slide 3

Steering Committee• Steve Black – DTE, Fredericksburg

District• Bill Bushman - VTRC• William Bywaters – MOM, Warrenton• John Coleman – Asst. Bridge Engineer,

Structures and Bridge Division• Roger Clatterbuck – Assistant to the

DME, Culpeper• Bob Gibson – District Maintenance

Engineer, Culpeper• Jose Gomez - VTRC• Jane Gunter – Assistant to the DME,

Staunton• Rob Hanson –VTRC• Dan Hinderliter – Budget Director,

Maintenance Division• Otis Hinton – Superintendent Fisherville

AHQ, Verona Res.• Lisa Hughes – Resident Engineer,

Martinsville

• Dan Liston – State Maintenance Engineer • Glenn McMillan – District Maintenance

Engineer, Fredricksburg• Joe Mitchell – MOM, Dillwyn Residency• Bob Moore – Resident Engineer,

Warrenton• Brooke Mullery – Training and

Development Coordinator - HRD• Dan Roosevelt – VTRC• Dennis Shea – IMMS Project Manager,

Maintenance Division• Jim Smith – District Maintenance

Engineer, Richmond• Kamal Suliman – District Traffic

Operations Director• Jerry VanLear – Resident Engineer,

Verona• Bruce Wilkerson – Facility Manager for

Monitor Merrimac Memorial Bridge Tunnel


Slide 4

Outline• Introduction

– Multiple Objective Aspects

• Data Collection

• Current Budget Allocation Process

• Concept for a Needs-Based Approach– Residency

– District/State Maintenance Office

• Extensions

• Discussion Questions


Slide 5

Introduction


Slide 6

Motivation“The future of maintenance lies clearly along the lines of asset management, investment strategy and sound business decisions. With competition for scarce resources a certainty of life, the adoption of asset management principles and the completion of the underlying support structures and management systems are key to future improvements in efficiency and productivity.”

- Governor’s Commission on Transportation Policy, Final Report, December 15, 2000


Slide 7

Motivation (cont.)

• Virginia’s maintenance expenditure in FY 2001 was $837M (MPLG Budget and Expenditure Report, 2001) and in FY 2000 was $762M (Governor’s Commission, 2000).

• Increase in maintenance cost is expected to continue into the future.

• Competition for scarce monetary resources is prevalent.

• There is a need to make timely decisions in order to maintain transportation assets.


Slide 8

Goal

Develop a risk-cost-benefit modeling and analysis framework to aid the management of maintenance of

Virginia roads and highways by the Virginia Department of Transportation


Slide 9

Efficacy of Risk Management

Cost of Maintenance without Risk Management

Cost

δ

Cost of Maintenance with Risk Management

∆

∆>>δ

Time


Slide 10

Multiobjective Trade-offAnalysis is at the Heart of

Risk Management

Risks, costs, and benefits are often measured in different units; nevertheless, to manage the system, an acceptable balance is sought.


Slide 11

As we advance into the Terra Incognita of tomorrow, it is better to have a generaland incomplete map, subject to revision and correction, than to have no map at all.

Alvin Toffler, Powershift, Bantam Books, 1990(author of Future Shock)


Slide 12

Technological AgeRisk Management ≈ Optimal Balance

Uncertain UncertainBenefits Costs

Technology Management:

Man/Machine/Software•Planning•Design

•Operation

RiskManagement


Slide 13

Risk Assessment and Management

Risk assessment and management must be an integral part of the decisionmaking process, rather than a gratuitous add-on technical analysis.


Slide 14

Risk

A Measure of the Probability andSeverity of Adverse Effects

William W. Lowrance, 1976


Slide 15

Risk vs. Safety• Measuring risk is an empirical, quantitative,

scientific activity (e.g., measuring the probability and severity of harm).

• Judging safety is judging the acceptability of risks – a normative, qualitative, political activity.

(After William W. Lowrance, 1976)


Slide 16

Importance of Risk Assessmentand Management

Those private and public organizations who can successfully address the risk inherent in their business – whether future use of chemicals,environmental protection, future product design, resource availability, natural forces, or the reliability ofman/machine systems will dominate the technologicalmarket.


Slide 17

System Failure

HardwareFailure

HumanFailure

OrganizationalFailure

SoftwareFailure

Risk: is a measure of theprobability and severity ofadverse effects

Measuring Risk: is anempirical, quantitative, scientific activity

Safety: is the level of riskthat is deemed acceptable

Judging Safety: is a normative, qualitative, political activity


Slide 18

System FailureOrganizational Failure

KnowledgeManagement

Human Failure

InformationAssurance

Hardware Failure Software Failure


Slide 19

Risk Assessment andManagement


Slide 20

Risk Assessment

Risk Assessment• What can go wrong? • What is the likelihood that it would go wrong? • What are the consequences?

[Kaplan and Garrick 1981].

Answers to these questions help risk analysts identify, measure, quantify, and evaluate risks and their consequences and impacts.


Slide 21

Risk Management

Risk Management• What can be done and what options are available?• What are the associated trade-offs in terms of all

costs, benefits, and risks? • What are the impacts of current management

decisions on future options? [Haimes 1991, 1998].

Answers to these questions help decisionmakers build on the risk assessment process and benefit from sound current and future policy options and their associated tradeoffs.


Slide 22

Multiple Objective Aspects


Slide 23

Multiobjective Decisionmaking

The Student Dilemma

{Grade Point Average

Income for Part-Time Work

Leisure Time

Maximize


Slide 24

100

200

300

400

500

10 20 30 40 50

$/wk

f1(•)

hr./wk

INCOME FROM PART-TIME WORK


Slide 25

10 20 4030 6050 70 hr./wk.

GPA AS A FUNCTION OF STUDYING TIME

GPA

0.0

1.0

2.0

3.0

4.0

f2(•)


Slide 26

600

0 10 20 30 40 50 60 70 80 90

GPA( )•

2f ( )•1f

$/wk

GPA AS A FUNCTION OF STUDYING TIME

INCOME FROM PART-TIME WORK90 80 70 60 50 40 30 20 10 0

INCOME

GPA

4.0 500

4003.0

300

2.0

200

1.0100

00.0


Slide 27

The Student Dilemma(Pareto Optimal Frontier)

700

600

100

Inco

me

($/w

eek)

200

400

300

500

04.000.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50

Grade Point Average


Slide 28

Data Collection


Slide 29

Meetings and Interviews• 12/18/01 – Bob Moore, Doug Bywaters, Warrenton

Residency• 12/21/01 – Malcolm Kerley, Structures and Bridge

Division• 12/21/01 – Dan Hinderliter, Maintenance Division• 2/15/02 – Doug Bywaters, Warrenton Residency• 3/5/02 – Roger Clatterbuck, Culpeper District• 3/5/02 – David Pierce, Culpeper District Bridge Office• Several meetings with VTRC staff and managers


Slide 30

Sample of Information Collected


Slide 31

Sample of Information Collected (cont.)


Slide 32

Current Budget Allocation Process


Slide 33

Current Budget Allocation Process

MPLG

State Maintenance Allocation

District Allocations

Residency Allocations

District

Special Sections

AreaHistorical District Allocations

Feedback

Area AllocationsDistrict

Residency

Residency AreaHistorical Allocations, Lane Mileage, Inventoried Structures, Bridge Inspections

Feedback

AreaHistorical Allocations, Bridge Inspections, Superintendent Input Superintendent

Assessments


Slide 34

Current Budget Allocation Process (cont.)

MPLG

NEGOTIATION

1 2 9j… …District

1 2 nk… …

BUDGET

Residency

Assets

Pavements(PMP)

Bridges(Pontis)

Others(ICAS)


Slide 35

Current Budget Allocation: MPLG

• Allocations to Districts are based on allocations of previous years.

• Adjustments are made considering state budgetary changes and changes in the maintenance burdens of the Districts.

• Decisions are made by consensus.


Slide 36

Current Budget Allocation: Culpeper District

• Culpeper District receives budget allocations from the MPLG for specific programs:– Base budget (95.1%)– Replacement of signs for all systems (1.0%)– Preventative maintenance bridges (0.6%)– Preventative maintenance pavements (1.2%)– Guardrail upgrades and replacements (1.3%)– Diamond grading rollup signs (0.4%)– Nationwide permits (0.2%)– Additional inventory (0.2%)


Slide 37

Current Budget Allocation: Culpeper District (cont.)

• The base budget consists of expenses for salaries, equipment, ferry, liquid calcium, mowing, litter control, landfill fees, fencing, tree and brush removal, hydroseeding, sign maintenance, and uniforms.

• The base budget also covers the expenses and salaries of the divisions: Structure and Bridge, Environmental, District Maintenance, Traffic Engineering, and Pavement Management.

• Excess funds are classified as funds for additional allocation.


Slide 38

Current Budget Allocation: Culpeper District (cont.)

• Culpeper District allocates the given budget using:– Lane miles

• Preventative Maintenance Pavements• Guardrail Upgrades and Replacement• Additional Inventory• Additional Allocation

– Number of inventoried structures• Preventative Maintenance Bridges

– Secondary lane miles• Sign Replacement


Slide 39

Current Budget Allocation: Warrenton Residency

• The Residency receives its budget from the District.

• The budget allocation is determined from historical and special needs for increased funding (determined by lane mileage and safety).

• The Residency then looks at the budget history of its area headquarters.


Slide 40

Current Budget Allocation: Warrenton Residency (cont.)

• Funds are allocated to the area headquarters based on past expenditures. Funding is typically increased by 5%.

• Funds are also allocated for maintenance, construction, and bridges. Any funds left over are used for sidewalks, gutters, culverts, guardrails, and others.


Slide 41

Current Budget Allocation: Warrenton Residency (cont.)

• Funds are allocated to each area for specific activities (e.g., patching and mowing).

• Remaining funds are allocated for specific assets (e.g., pavement replacements). Budget tradeoffs are made on a daily basis. The decision horizon is usually one month.


Slide 42

Challenges and Opportunities

• Develop an allocation system that is driven by the needs of Residencies and Districts such that the allocation is directed to areas where it achieves greatest benefit

• Incorporate engineering and economic principles to determine actions that result in least life-cycle costs


Slide 43

Challenges and Opportunities (cont.)

• Perform trade-offs among competing objectives (e.g., immediate (short-term) cost and long-term costs)

• Identify extreme events that influence maintenance and vice versa


Slide 44

Challenges and Opportunities (cont.)

• Knowledge-management• Technology transfer• Training• Improved communications• Effective use of databases (e.g., ICAS,

PMP, BMS) and decision tools (e.g., trade-offs, decision trees, and probabilities)


Slide 45

Concept for a Needs-Based Approach


Slide 46

Needs-Based Approach

MPLG


1 2 nk… …Residency

Assets

Pavements (PMP)

Bridges(Pontis)

Others(ICAS)

BUDGET

NEEDS


Slide 47

Needs-Based Approach (cont.)

Needs Assessment

Identification of Maintenance Options

Evaluation of Maintenance Options

Filtering of Maintenance Options

Aggregation of Maintenance Options

Evaluation of Maintenance Policies


Slide 48

Needs-Based Approach (cont.)

Pavements (PMP)Bridges (BMS) Needs Assessment Others (ICAS)

Identification of Maintenance Options

Pavement Management Program

Bridge Management System (Pontis)Evaluation of Maintenance OptionsDecision Trees

Threshold Values Filtering of Maintenance Options


Set of viable policiesEvaluation of Maintenance Policies


Slide 49

Needs-Based Approach (cont.)Short-term Cost, Long-term cost, Average Condition

Maintenance OptionsPMP

Residency Staff

Pontis

ICAS

Visual Inspections

Level of Service Requirements, Policies

Modeling Option Aggregation

Viable Sets of Maintenance Options

Allocation Recommendations

Option EvaluationFeedback Budget


Slide 50

Definition of Maintenance Policy

A policy is an aggregation of

maintenance options for all assets

under consideration.


Slide 51

Principle for Evaluation of Maintenance Options

Short-term Cost

∆ Cost

Long-term Cost (NPV)∆ Cost


Slide 52

Viable (Pareto optimal) Pavement Options

Pareto Optimal Pavement Policies

$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

$- $10 $20 $30 $40 $50 $60 $70 $80 $90 $100

Long-term Cost (Annualized, thousands)

Shor

t-ter

m C

ost (

thou

sand

s)


Slide 53

Evaluation of Maintenance Options

• Primary objectives

*6-year horizon is used

Criteria Metric

Short-term cost Immediate cost; Cost of maintenance action for current year

Long-term cost Expected net present value of the cost of a sequence of future maintenance actions

Condition Expected average condition over a set horizon


Slide 54

Evaluation of Maintenance Options (cont.)

• Applying these three objectives enables us to only consider those combinations of maintenance options that meet cost and performance constraints.

• In finding the viable set of policies, we employ only two objectives: long-term cost and short-term cost.


Slide 55


• When we assume a minimum level-of-service requirement for the highway system, long-term costs fall as average condition rises.

• Therefore, long-term cost and condition are not conflicting, and we only need one to find the viable (Pareto optimal) set.


Slide 56


• Secondary objectivesCriteria Metric

Ride quality Performance Capacity sufficiency Safety Change in accident rate

Reliability Probability of design requirements shortfall

Ride quality Traffic disruption Local acceptance

Customer satisfaction

Public opinion Detour length Accessibility Local (area) importance

Average daily traffic Economic benefit Network importance Appearance Appearance improvement


Slide 57

Approach Overview: Residency

Residency Staff

Maintenance Options

Options Modeling

Options EvaluationDatabase

PMPBMS(Pontis)ICAS

1. Option A2. Option B3. Do Nothing

1. Option A2. Option B3. Do Nothing

Pavement Management Program

Bridge Management System (Pontis)


Slide 58

Approach Overview: District/MPLG

District/MPLG Staff

Policy Aggregation and Tradeoff AnalysisOptions Evaluation

Residencies/Districts


Slide 59

Approach Overview: MPLG

Policy Aggregation and Tradeoff Analysis MPLG Budgeting

Budget----------- $----------- $----------- $


Slide 60

Approach Overview: Feedback and Fine-Tuning

MPLG


Residency 1 2 nk… …


Slide 61

Residency: Step-by-Step


Slide 62

Approach Details: Residency

B1Asset Condition

Area Supervisor

Needs Assessment

B1

B3

B2Option 1 - Repaint

Option 2 – Do Nothing

B3 Option 1 - Resurface

B4



Slide 63

Approach Details: Residency (cont.)

Consider Asset B1

Option 1 - Repaint


Primary Objectives Long-

term $Long-term $

Condition

Size = Short-term $

Short-term $

Secondary Objectives + Priority Level

Risk Fingerprinting


Slide 64

Approach Details: Residency (cont.)% Completed

Long –term $ Size =

Short-term $

Condition

Priority1 2 3

+ Priority Level

Long-term $

Condition

Size = Short-term $

+ Priority Level

Long-term $

Condition

Size = Short-term $

DistrictDifferent Assets

+ Priority Info

Long-term $

Condition

Size = Short-term $

Resident Engineer


Slide 65

Examples of Identification of Maintenance Options

• Crack sealing– application of a sealing material directly into the cracks or joints

• Fog seals– application of material sprayed directly on surface of existing

pavement

• Chip seals– spray application of binder immediately covered by a layer of

one-sized or graded aggregate

• Thin cold-mix seals– application of mixtures of emulsions, aggregates, portland

cement, and chemicals directly on pavement


Slide 66

Examples of Identification of Maintenance Options (cont.)

Pontis Bridge Management System• We can use the database contained in Pontis to

predict future conditions of bridge elements and determine maintenance needs over a fixed horizon.

• We can also use Pontis to analyze preservation and improvement options for bridges.


Slide 67


Multiobjective Decision Tree• Composed of decision nodes and chance nodes• Each pairing of an alternative and a state of nature is

characterized by a vector-valued performance measure.

Maintenance Options

Scenarios short-term ,cost

long-termcost


Slide 68


• We use PMP, BMS (Pontis), and decision trees to look at different maintenance scenarios that can occur over a specified horizon.

• With these systems, we can determine short-and long-term maintenance costs and asset condition for each scenario.


Slide 69

Principle for Evaluation of Maintenance Options

Short-term Cost

∆ Cost

Long-term Cost (NPV)∆ Cost


Slide 70

Filtering of Maintenance Options: Risk Fingerprinting

ADT Detour Network Importance

Local Importance

High Priority Filter


Local Importance

Low Priority Filter


Slide 71

Filtering of Maintenance Options: Risk Fingerprinting (cont.)


Local Importance

Option 1


Local Importance

Option 2


Slide 72


Option 1- High Filter


LoImportance

cal

High Priority


Slide 73



Local Importance

Option 2 – High Filter


Local Importance

Option 2 – Low Filter

Medium Priority


Slide 74


HighHighHighHighHighHighLocal Importance

LowLowLowLowLowLowNetwork Importance

DecreaseIncreaseDecreaseIncreaseDecreaseIncreaseRide Quality

111122Detour Length (miles)

65065010001000500500ADT

N/AMedN/AHighN/AMedPriority

436492405463470495Long-Term Condition

99541188713599Long-Term Cost (thousand)

020035040Short-Term Cost (thousand)

Defer2” ACDefer2” ACDefer2” ACOption

Pavement 3 (0.4 mi) Pavement 2 (0.6 mi) Pavement 1 (0.9 mi) Asset


Slide 75

Aggregation of Maintenance Options (cont.)

• We are concerned with the aggregate performance and costs of the highway system. Therefore, we should examine combinations of maintenance options.

• By examining the possible combinations of options, we can find maintenance policies that fall within budgetary and performance constraints.


Slide 76

Aggregation of Maintenance Options: Example

• Assume we have two sections of pavement with the following options

$30,000AC MixPavement 1

$0Do Nothing

$22,000AC MixPavement 2

$0Do Nothing


Slide 77

Aggregation of Maintenance Options: Example (cont.)

• From these possible actions we can generate four possible policy options, each with its own cost.

0Do NothingDo Nothing4

22000AC MixDo Nothing3

30000Do NothingAC Mix2

52000AC MixAC Mix1

CostPavement 2 ActionPavement 1 ActionPolicy


Slide 78


• The previous example illustrates the basic option aggregation procedure. In order to make it complete, however, there are two additions to the process:– We do not just consider a single maintenance action

on a particular asset. Rather we look at series of actions taken on that asset over time.

– We examine the policies in terms of both their short-term cost and their long-term cost.


Slide 79


• We should eliminate policies that are dominated (i.e., there is another policy that outperforms it in every way).

• We are left with the viable (Pareto optimal) set of possible maintenance policies.


Slide 80


Short Term Cost

DOMINATED Maintenance Policy

Long Term Cost


Slide 81

Obj 1

Obj 2


Assets 1, 2, 3, & 4

Obj 1 Obj 1

Assets 3 & 4Assets 1 & 2

Obj 2 Obj 2

Obj 1 Obj 1 Obj 1 Obj 1

Obj 2 Obj 2 Obj 2 Obj 2

Asset 1 Asset 2 Asset 3 Asset 4


Slide 82


• After the aggregation, we should end up with an output like the following (six year horizon):

• All of these policies are viable (Pareto optimal) and we can plot them in order to see the tradeoffs.

240952” AC2” AC2” AC5

272602” ACDefer2” AC4

276552” AC2” ACDefer3

308202” ACDeferDefer2

353-DeferDeferDefer1

Long-Term Cost (thousand)

Short-Term Cost (thousand)Pavement 3Pavement 2Pavement 1Policy


Slide 83

Viable (Pareto optimal) Pavement Options


$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

$200 $220 $240 $260 $280 $300 $320 $340 $360 $380

Long-term Cost (NPV, thousands)

Shor

t-ter

m C

ost (

thou

sand

s)


Slide 84

Viable (Pareto optimal) Pavement Options (cont.)


$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

$- $10 $20 $30 $40 $50 $60 $70 $80 $90 $100

Long-term Cost (Annualized, thousands)

Shor

t-ter

m C

ost (

thou

sand

s)


Slide 85


• We may also look at the average pavement conditions that result from these policies.

• We can plot the average pavement condition as the bubble size in a bubble chart.

81240952” AC2” AC2” AC5

77272602” ACDefer2” AC4

79276552” AC2” ACDefer3

76308202” ACDeferDefer2

73353-DeferDeferDefer1

Long-Term Ave. Condition

Long-Term Cost (thousand)

Short-Term Cost

(thousand)

Pavement 3Pavement 2Pavement 1Policy


Slide 86

Pavement Options with Conditions


$-

$20

$40

$60

$80

$100

$120

$200 $220 $240 $260 $280 $300 $320 $340 $360 $380

Thou

sand

s

Thousands

Long-term Cost (NPV)

Shor

t-ter

m C

ost

73

76

79

77

81


Slide 87

District/State Maintenance Office: Step-by-Step


Slide 88

Approach Details: District/State Maintenance Office

% Completed

Long –term $ Size =

Short-term $

Condition

Priority1 2 3

District/ State Maintenance Office Staff

+ Priority Info

Long-term $

Condition

Size = Short-term $

+ Priority Info

Long-term $

Condition

Size = Short-term $

+ Priority Info

Long-term $

Condition

Size = Short-term $

Residencies / Districts


Slide 89


The aggregation of maintenance options occurs at the residency level, the district level, and the

state level.


Slide 90

Evaluation of Maintenance Policies

• Once we have selected a set of candidate policies, we can compare them in terms of their costs, predicted asset conditions, accomplishment of priorities, and accomplishment on the secondary metrics.


Slide 91

Evaluation of Maintenance Policies:Demonstration

• For illustration purposes, we simulated two maintenance policies for the district level using a six-year horizon.

• Let us assume that we are comparing two policies and we are primarily concerned with priority accomplishment and ride quality. The following charts show how we could compare these policies.


Slide 92

Evaluation of Maintenance Policies: Demonstration (cont.)

Policy Comparison - Priority Accomplishment

0102030405060708090

100

High PriorityAccomplishment

(%)

Med PriorityAccomplishment

(%)

Low PriorityAccomplishment

(%)

% o

f Tas

ks A

chie

ved

Option 1Option 2


Slide 93


Policy Comparison - Ride Quality

0

10

20

30

40

50

60

70

80

90

100

Decreases Same Increases

% o

f Mai

nten

ance

Act

ions

Option 1Option 2


Slide 94

Evaluation of Maintenance Policies Demonstration (cont.)

• These are just two possible evaluation criteria. The following are examples of other possible information that can be derived for an a particular maintenance policy.


Slide 95


Short Term Cost ($ million) 60Long Term Cost (NPV, $ million) 485Long Term Avg Bridge Condition 80Long Term Avg Road Condition 74High Priority Accomplishment (%) 85Med Priority Accomplishment (%) 60Low Priority Accomplishment (%) 20

Bridge High Priority Accomplishment (%) 87Bridge Med Priority Accomplishment (%) 55Bridge Low Priority Accomplishment (%) 18

Road High Priority Accomplishment (%) 84Road Med Priority Accomplishment (%) 63Road Low Priority Accomplishment (%) 21


Slide 96


Policy 1 - Bridge Priority Accomplishment

0102030405060708090

100

Bridge High PriorityAccomplishment (%)

Bridge Med PriorityAccomplishment (%)

Bridge Low PriorityAccomplishment (%)

% o

f Tas

ks A

chie

ved

Policy 1 - Road Priority Accomplishment

0102030405060708090

100

Road High PriorityAccomplishment (%)

Road Med PriorityAccomplishment (%)

Road Low PriorityAccomplishment (%)

% o

f Tas

ks A

chie

ved


Slide 97


Network Importance

0

20

40

60

80

100

Low Med High

Ride Quality

0

20

40

60

80

100

Decreases Same Increases

Public Opinion

0

20

40

60

80

100

Unfavorable Indifferent Favorable

Local Importance

0

20

40

60

80

100

Low Med High


Slide 98


Residency Charlottesville Culpeper Louisa WarrentonBudget (million $)Bridges 7 8 5 7Roads 4 5 4 5Total 11 13 9 12Long Term CostBridges 57 64 40 56Roads 32 40 32 40Total 89 104 72 96Long Term ConditionBridges Avg 83 78 75 85Roads Avg 75 73 72 77


Slide 99


Residency Charlottesville Culpeper Louisa WarrentonPrioritiesBridges High 85 86 90 88Bridges Med 50 58 60 55Bridges Low 10 11 22 30Roads High 87 88 78 83Roads Med 55 60 65 69Roads Low 18 20 22 23Total High 84 86 87 84Total Med 58 60 63 60Total Low 23 10 40 13ADTBridges 30025 9125 8735 10705Roads 52000 15000 10000 46000Total 82025 24125 18735 56705DetourBridges 25 172 221 149Roads 30 42 50 32Total 55 214 271 181


Slide 100


Long Term Expected Road Condtion

0102030405060708090

100

Charlottesville Culpeper Louisa Warrenton

Long Term Expected Bridge Condtion

0102030405060708090

100



Slide 101


Charlottesville Priority Accomplishment

0

10

20

30

40

50

60

70

80

90

100

High Med Low

% A

chie

ved

Louisa Priority Accomplishment

0

10

20

30

40

50

60

70

80

90

100

High Med Low

% A

chie

ved

Culpeper Priority Accomplishment

0

10

20

30

40

50

60

70

80

90

100

High Med Low

% A

chie

ved

Warrenton Priority Accomplishment

0

10

20

30

40

50

60

70

80

90

100

High Med Low

% A

chie

ved


Slide 102


Residency Allocations

0

2

4

6

8

10

12

14



Slide 103

MPLG

Decision Making Process


Slide 104

Extensions


Slide 105

Extensions

• Evaluate methods for combining and performing trade-offs among bridge and pavement policies

• Add uncertainty intervals to cost and condition estimates

• Introduce consideration of extreme events• Introduce risk metrics to the prioritization

procedure


Slide 106

Discussion Questions


Slide 107

Discussion Questions

• Knowledge Based Questions1. How do engineers and other VDOT personnel

communicate within a residency? Among residencies within a district? Among districts?

2. Do you share information? How do you share experiences? Do you meet once a month or occasionally to compare experiences?

3. How do people from maintenance deal with people in other divisions (e.g., construction)?


Slide 108

Discussion Questions (cont.)

• Knowledge Based Questions (cont.)4. How do you ensure that experiences and

knowledge in one district is transferred and utilized by other districts?

5. What do you do to promote continuing education and training of engineers and staff?

6. What do we (UVA) need to do in order to start developing people who can use what we have developed?


Slide 109


• Data collection7. Is there a relationship between long-term cost (total

cost associated with a series of maintenance actions over a fixed horizon) and asset condition?

8. Can you suggest topics or areas for case study or demonstration purposes that balance short-term and long-term maintenance costs?

9. Where can we get data on maintenance actions and costs (per sq. yd. or per mi.) to use for demonstration purposes?


Slide 110


• Data collection (cont.)10. How are the probabilities used in Pontis obtained?

Are there probabilities for other assets (e.g., roads, signs, and pipes)?

11. Do you feel that the experience with VMS was beneficial? Is there anything that we can learn from the VMS experience?


Slide 111

Discussion Questions (cont.)• Data collection (cont.)

12. These are some objectives that can be used to evaluate maintenance options. Are these sufficient? What other objectives can you suggest?

Criteria M etric Ride quality Performance Capacity sufficiency

Safety Change in accident rate

Reliability Probability of design requirements shortfall

Ride quality Traffic disruption Local acceptance

Customer satisfaction

Public opinion Detour length Accessibility Local (area) importance

Average daily traffic Economic benefit Network importance Appearance Appearance improvement


Slide 112


• Risk Management13. How can you help to identify a range of

unexpected and/or undetected conditions that can have an impact to maintenance activities at facility, Residency, District, and statewide levels (e.g., heavy snow seasons, other weather patterns, actions of other agencies, financial stringencies)?

14. How can you help to characterize the impacts of the conditions above (Question 13)?

15. How can you help to generate policy options to mitigate the conditions above (Question 13)?


Slide 113


• Risk Management (cont.)16. How can you help to identify benefit-to-cost

measurements in order to evaluate the policy options above (Question 13)?

17. How can you help to identify the influence of maintenance activities to the potential occurrence of extreme conditions at facility, Residency, District, and statewide levels (e.g., lane or bridge closures due to unforeseen or undetected deterioration of structures or pavements)?

18. How can you help to characterize the impacts of the conditions above (Question 17)?


Slide 114


• Risk Management (cont.)19. How can you help to generate policy options to

mitigate the conditions above (Question 17)?20. How can you help to identify benefit-to-cost

measurements in order to evaluate the policy options above (Question 17)?

21. How can you help to identify a range of alternative maintenance policies at facility, Residency, District, and statewide levels?


Slide 115


• Risk Management (cont.)22. How can you help to estimate the short-term costs

of implementing the above maintenance policies (Question 21)?

23. How can you help to characterize the potential lifecycle costs (where incurred, when incurred, to whom, under what conditions) of the above maintenance policies (Question 21)?

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