Road Asset Management
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1 Road Asset Management Raja Shekharan, Ph.D., P.E. Virginia Department of Transportation National Workshop on Modern Trends in Pavement Engineering IISc, Bangalore July 15, 2011
2 Transportation Asset Management - Definition Transportation Asset Management is a strategic and systematic process of operating, maintaining, upgrading and expanding physical assets effectively throughout their life cycle. It focuses on business and engineering practices for resource allocation and utilization, with the objective of better decision making based upon quality information and well defined objectives. - AASHTO Transportation Asset Management Guide, 2011
3 Transportation Asset Management A business model, a decision support system and a management approach that addresses (AASHTO Transportation Asset Management Guide): What is the current state of physical assets? What are the required levels of service and performance delivery? Which assets are critical to sustained performance? What are the best investment strategies for operations, maintenance, replacements, and improvement? What is the best long-term funding strategy?
4 Asset Management Methodology Manage assets using a life-cycle analysis approach Use a Needs Based Budget approach to identify and prioritize maintenance and operations needs based on the inventory and condition assessments Employ processes to plan, budget, implement, monitor and measure performance
5 Maintenance The focus of maintenance is on physical assets Interstate, Primary, Secondary Roads Roads Tunnels Bridges Rest Areas Roadside
6 Operations The focus of operations is on movement of traffic Ops Centers Cameras Incident Mgt Messaging
7 AASHTO Guide to Transportation Asset Management
8 Asset Management Program The Business Process
9 Incremental Development Methodology Also known as Spiral Iterative Evolutionary Progressive Extreme RUP (IBM) etc.
10 Budget Process Cycle Data Collection Analysis Planning Needs-based Budget District Allocations Work Activities
11 Modules of Asset Management System PMS, BMS, RCA Needs Based Budget Planning Module Work Accomplishments Inventory Analysis Tools
12 Pavement Management
13 Pavement Condition Data Collection Length Total yearly collection: approx. 32,600 directional km Interstate: approx. 3,500 directional km (100% of IS system) Primary: approx. 16,800 directional km (100% of PR system) Secondary: approx. 12,300 directional miles (~20% of SC system) SC system is on a 5-year collection cycle
14 Pavement Condition Data Collection and Analysis Program Data Collection & QA Control Sites Production Data Collection Contractor s QC (RWG) Independent Verification & Validation (QES) QA by VDOT Database Acceptance Pavement Condition Database Data loaded in PMS Data Analysis & Reporting System Condition Ride Quality State of the Pavement Report Legislative Reports HPMS Reports GIS Maps Unconstrained Needs Analysis Define M&R Activities Extract Unit Costs from TRNS*PORT Decision Matrices Unconstrained Needs Estimation Network Optimization Set Performance Targets & Goals Develop Perf. Prediction Models Optimization Performance based needs Allocation Distribution
15 Photolog Single view Panoramic view 1300 x 1030 pixel 1920 x 1080 (HDTV) Direct-to-digital Custom angles Geometry & Spatial Inertial measurement unit HPMS curve type Long. Grade Cross slope Centerline mapping Spatial referencing for GIS integration Data Collection Equipment Capabilities Pavement Image recognition software Strobe-lit pavement video Roughness Texture Rutting Surface Distress Ground Penetrating Radar Assets Inventory from imagery Location determined Offset measured Height and width measured Sign code recorded Condition assessment
16 Distance Measuring Instrument (DMI) DMI utilizes a precision optical shaft encoder that is mounted on the left rear driving wheel. The DMI records 2,000 pulses per revolution. Accuracy is ±0.02% of the linear distance traveled. Ensures accurate low speed roughness measurements down to 20 km/h (12.5 mph).
17 Pavement Images Rear downward facing cameras Continuous pavement images of full lane width Renders pavement distresses down to 2mm (0.08 inches) in width
18 Pavement Distress Marking
19 Laser Rut Measuring System Pair of rear mounted INO Lasers Measure full transverse profile of the road surface to over 1,200 points Transverse profile is evaluated to determine the depths of ruts
20 International Roughness Index (IRI) Laser SDP System 16 khz laser in each wheelpath Measures continuous longitudinal profile of the roadway
21 High Definition Right of Way Images True High Definition 1920 x 1080 CCD Camera Wide angle High Definition images A single image every 21 feet (variable)
22 GPS Data Trimble System Applanix POSLV (Position and Orientation System) Collected every station interval Two antennas to give vehicle heading
23 GPS Data Real Time GPS Data Collection to ensure proper collection and referencing. Inertial referencing system allows for fill in of missing GPS data.
24 Automated Distress Surveys Project Quality Process Daily/Weekly checks Control Sites Production data collection checks Independent Verification and Validation Data Acceptance checks
25 Software to View Data
26 Data Reporting Reporting of Condition Data Statistics: Percent/Lane-Miles Deficient Condition Distributions Density of Key Distresses GIS Maps Distribution of Condition on Network (E, G, F, P, VP) Interstate Asphalt Pavement - Transverse Cracking (% of total area ) 0.0% 0.1% 0.4% 0.0% 0.2% 0.7% 0.0% 0.3% 0.7% 0.0% 0.3% 1.0% 0.2% 0.6% 1.1% 0.1% 0.3% 0.5% 0.0% 0.1% 0.4% 0.1% 0.3% 0.9% 1/BR 2/SA 4/RI 5/HR 6/FR 7/CU 8/ST 9/NO Severity Level 1 Severity Level 2 Severity Level 3 Project and Treatment Selection Type and Distribution of Distress on Pavement
27
28 Needs Analysis Two Types of Needs Analysis Unconstrained Provides a recommended treatment for entire network Based on network condition data and augmented using Age, Traffic and FWD Data Network Optimization Uses performance target to optimize treatment recommendations for budgeting and allocation
29 Maintenance Activity Categories Do Nothing (DN) Preventive Maintenance (PM) Corrective Maintenance (CM) Restorative Maintenance (RM) Major Rehabilitation/Reconstruction (RC)
30 Framework for Treatment Selection Pavement Surface Distresses Fatigue Cracking Transverse Cracking Patching Decision Matrices Preliminary Treatment Selection Decision Trees Final Treatment Selection Rutting Potholes Traffic Level Structural + + Integrity Capacity Construction History
31 Unconstrained Needs Decision Matrix Alligator Cracking Frequency Rare Alligator Cracking Severity NS Severe Very Severe Alligator Cracking Rutting Freq. N <10% >10% N <10% >10% N <10% >10% Rutting Sevrty <0.5" >0.5" <0.5" >0.5" <0.5" >0.5" <0.5" >0.5" <0.5" >0.5" <0.5" >0.5" Frequency <0.5" >0.5" <0.5" >0.5" <0.5" >0.5" P0 DN DN DN CM CM RM DN DN DN CM CM RM CM CM CM CM CM RM P1 DN DN DN CM CM RM DN DN PM CM CM Alligator RM CM Cracking CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC Severity CM CM CM RM RM RC P0 DN DN DN CM CM RM DN DN DN CM CM RM CM CM CM CM CM RM P1 DN DN DN CM CM RM DN DN PM CM CM RM CM CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC CM CM CM RM RM RC Rutting Sevrty P0 CM CM CM CM CM RM CM CM CM CM CM RM CM CM CM CM CM RM P1 CM CM CM CM CM RM CM CM CM CM CM RM CM CM CM CM CM RM P2 RM RM RM RM RM RC RM RM RM RM RM RC RM RM RM RM RM RC P0 DN DN DN CM CM RM DN DN DN CM CM RM CM CM CM CM CM RM P1 DN DN DN CM CM RM DN DN PM CM CM RM CM CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC CM CM CM RM RM RC P0 DN DN DN CM CM RM DN DN DN CM CM RM CM CM CM CM CM RM P1 DN DN DN CM CM RM PM PM PM CM CM RM CM CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC CM CM CM RM RM RC P0 RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM P1 RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM RM P2 RM RM RM RM RM RC RM RM RM RM RM RC RM RM RM RM RM RC P0 DN DN DN CM CM RM DN DN DN CM CM RM CM CM CM CM CM RM P1 DN DN DN CM CM RM DN DN PM CM CM RM CM CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC CM CM CM RM RM RC P0 PM PM PM CM CM RM PM PM PM CM CM RM CM CM CM CM CM RM P1 PM PM PM CM CM RM PM PM PM CM CM RM CM CM CM CM CM RM P2 RM RM RM RM RM RC RM RM RM RM RM RC RM RM RM RM RM RC P0 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC P1 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC P2 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC P0 PM PM PM CM CM RM PM PM PM CM CM RM CM CM CM CM CM RM P1 PM PM PM CM CM RM PM PM PM CM CM RM CM CM CM CM CM RM P2 CM CM CM RM RM RC CM CM CM RM RM RC CM CM CM RM RM RC P0 CM CM CM CM RM RM CM CM CM CM RM RM CM CM CM CM RM RM P1 CM CM CM CM RM RM CM CM CM CM RM RM CM CM CM CM RM RM P2 RM RM RM RM RM RC RM RM RM RM RM RC RM RM RM RM RM RC P0 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC P1 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC P2 RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC RC Transverse cracks per mile >=200 NS S VS NS VS S NS VS S NS VS S NS Rutting Freq. N <10% <0.5" >0.5" <0.5" >0.5" <0 P0 DN DN DN CM C P1 DN DN DN CM C P2 CM CM CM RM RM P0 DN DN DN CM C P1 DN DN DN CM C P2 CM CM CM RM RM P0 CM CM CM CM C P1 CM CM CM CM C 0-50 NS S S
32 Performance Based Needs Optimization Collect and apply condition data to management sections Utilize pavement condition prediction models Use criteria for pavement maintenance activity selection Establish performance measures and targets Create planning scenarios and run optimizations Determine performance based needs
33 Performance Based Budgeting Optimization Single Year, Multi-Constraint Optimization Optimization of maintenance activities on pavement management sections to achieve the objective function against multiple constraints for one year at a time Multi-Year, Multi-Constraint Optimization Optimization of maintenance strategies on a set of pavement management sections to achieve the objective function against multiple constraints over multiple years
34 Multi-Constraint Optimization Objective Functions Two types of objective functions available Minimize Cost Maximize Benefit (or other condition indicator) Pavement Condition Index Trigger Limit Min. Performance Existing Pavement Performance Predicted Pavement Performance Benefit Age
35 Optimization Results % Deficient % of Pavement Network in Deficient Condition by Lane Mile 25.0% % Deficient 23.0% 21.0% 19.0% 17.0% 15.0% FY Baseline-10% Baseline Baseline+10% Baseline+20%
36 Optimization Results % Needing Reconstruction % of Pavement Network Needing Reconstruction by Lane Mile 20.0% % Needing RC 15.0% 10.0% 5.0% 0.0% FY Baseline-10% Baseline Baseline+10% Baseline+20%
37 Optimization Results Average LM-Weighted CCI Pavement Network Average CCI by Lane Mile 80.0 Average CCI FY Baseline-10% Baseline Baseline+10% Baseline+20%
38 Bridge Management
39 Bridge Management VDOT maintains 19,356 structures, including 11,930 bridges and 7,426 large culverts. Structures receive routine inspections. The inspection quantifies the condition of the structure and provides a basis for determining asset needs. AASHTO Pontis bridge management system software is used to process inspection data and perform network-level analysis for needs based budgeting.
40 Data Collection Federal regulations mandate the inventory and inspection of structures and the annual reporting of data to the National Bridge Inventory (NBI). Each structure is inspected at regular intervals by qualified Bridge Safety Inspectors in accordance with the requirements of the National Bridge Inspection Standards (NBIS). Typically, a structure is inspected once every two years.
41 Determining Needs Pontis application software is used to analyze the needs of the bridge and large culvert assets. A program simulation using a predefined funding scenario is modeled to determine the unconstrained, unmet, preservation needs of structures. In general, Pontis recommends the most beneficial action/treatment based on level of funding, element condition, probabilistic deterioration trends and the cost of action/treatment.
42 Other Assets
43 RCA Stands for Random Condition Assessment Establishes a statewide inventory and condition assessment by extrapolation of randomly selected and surveyed samples Does not include mainline pavements and bridges RCA assets constitute approximately 15% of total unconstrained needs
44 Assets Included in the RCA Survey Pipes and Small Culverts Guardrails Guardrail Terminals Traffic Signs Pavement Markings Paved Ditches Unpaved Ditches Unpaved Shoulders
45 Planning Module
46 Planning - Inputs Parameters Extrapolation Factors Deterioration Rates Planning Module Condition and Inventory Pavement actual quantities RCA Assets sampled quantities Total Asset Quantities Asset Repair Quantities Regional Cost Factors Inflation Factor Ordinary Maintenance Corrective Replacement Rehabilitation Asset Repair Costs
47 Planning - Outputs Including Total Asset Quantities Starting Repair Quantities Annual Work Quantities Planning Module High Level Maintenance Plan (1 6 years) Annual Work Costs By... District Roadway System Asset Repair Group
48 Planning Module - Output In terms of the NBB process, the Planning Module produces Planning Module Total Unmet Needs Cost to Maintain Current Condition For pavements and RCA assets
49 Determining Unconstrained Needs Modeled Assets flexible and rigid pavements, ditches, cross pipes, unpaved shoulders, guardrail, end terminals, traffic signs, paved shoulders, nonhard surface roads, bridges and large culverts, traffic signals, overhead signs, smart traffic centers, tunnels, ferries, rest areas, moveable bridges Non-Modeled Assets roadside assets, retaining walls, drainage, traffic devices, facilities Cost Centers and Programs snow prep and removal, equipment rental, etc.
50 Asset Management Maturity Scale AASHTO 2011 TAM Maturity Scale Level Initial Awakening Structured Proficient Best Practice General Description No systematic processes in place and little motivation to improve existing processes. Recognition of the need for more systematic processes and data collection activities. Efforts at this level typically rely on one or more champions. Processes and tools developed. There is a shared understanding and motivation that results in coordination of activities. Asset management strategies, processes, and tools provide information to establish agency expectations and accountability. Asset management strategies, processes, and tools support decisions and are regularly evaluated and improved.
51 Why Asset Management? Successful implementation of Transportation Asset Management (TAM) is fundamentally about good management, effective leadership, and achieving the right organizational culture. It does not happen overnight, and requires consistent direction, focus, and attention over time. AASHTO 2011
52 Thank You
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