U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
Four of the sites the scan team visited represented asset management experience at the state or provincial government level. In the case of both countries visited, the federal government is not a major player in asset management, providing much less funding than the United States for transportation infrastructure. In Australia, for example, the federal government is proposing to remove itself even more from funding transportation systems. Thus, the states and provinces visited had a great deal of autonomy in developing asset management programs in ways that met their own needs. The four state/provincial government experiences with asset management included those for Alberta (Canada), and New South Wales, Queensland, and Victoria (Australia).
Alberta Infrastructure and Transportation (AIT)—www.inftra.gov.ab.ca
Infrastructure Managed
|
With just under 3 million people, Alberta is one of the wealthiest provinces in Canada, primarily because of its vast reserves of natural resources. Approximately the size of Texas, Alberta has a large road network that, because of wide temperature fluctuations and significant heavy truck use, experiences substantial preservation and maintenance needs. Critical transportation issues identified by Alberta transportation officials include 1) an aging existing infrastructure, 2) demands for new corridors (e.g., ring roads) around major cities, 3) a new fiscal framework on public-private partnerships, and 4) increasing competition for resources from other government ministries and for other types of infrastructure.
With an annual budget of just over Can$4 billion (US$3.2 billion), Alberta Infrastructure and Transportation (AIT) is responsible for overseeing not only the road network, but also other major types of infrastructure in the province. Partly because of this multiple responsibility, the scan team was particularly interested in seeing how the province established priorities among different asset categories. In addition, AIT's reputation for conducting state-of-the-art asset management provided an important motivation for this scanning study, a reputation supported by the team's observations.
Several factors have influenced AIT's development of a comprehensive asset management program. Perhaps most important were economic worries in the late 1980s and early 1990s that put pressure on the government to downsize and become more efficient. By the mid-1990s, this led AIT to outsource much of its maintenance and capital renewal activity (planning, design, construction supervision, and maintenance operations) to private companies. This resulted in an AIT staff reduction from about 2,500 to less than 800 employees. With such a structure for program delivery, however, AIT officials realized that a process for systematically identifying deficiencies and allocating resources was an important part of its asset stewardship responsibilities. An asset management program was viewed as serving this function. In fact, AIT officials credit the agency's infrastructure management systems with establishing a credible maintenance backlog estimate of Can$3.3 billion (US$2.6 billion) that was accepted by government officials as the “real” infrastructure need in the province. The desire for an effective asset management program also occurred about the same time as AIT's pavement and bridge legacy management systems needed to be upgraded.
The evolution of government policy toward infrastructure has also had an important influence on the evolution of asset management practice in AIT. In the late 1990s, a policy of encouraging more coordinated capital planning was adopted, which in 1999 was incorporated into the government's business plan. In 2002, the government adopted a policy on alternative capital delivery mechanisms, which included encouraging public-private partnerships as a means of providing more infrastructure. Eliminating the maintenance backlog, which at the time was about Can$1 billion (US$800 million), became a priority. In 2003, the first 3-year capital program under this new fiscal management structure was adopted, which was supported by a 5-year capital plan, a 10-year strategic plan, and a 25-year futures plan. Asset management was a critical theme in all of the plans; indeed, the decision support structure provided by AIT's information systems was critical in the development of many of the strategies.
“Transportation infrastructure is not an expenditure; transportation infrastructure is an investment.”
— AIT official
Although not exactly a driver for asset management, one reason AIT has been able to show such progress in its asset management program is the continuity in top leadership. The same political party has been in power since 1971, and government ministers responsible for AIT have had long tenures. This continuity in leadership, along with a policy of adopting business practices for governmental operations, has led to asset management techniques becoming part of the strategic management of the agency.
This combination of seeking greater financial efficiency in program delivery, providing oversight for outsourced functions, and the need to update its legacy systems led AIT to develop a comprehensive asset management system called the Transportation Infrastructure Management System (TIMS).
The asset management function in AIT is evolving. A small section in headquarters, the highway asset management section, deals primarily with high-level performance measure development, target setting, and reporting, and provides data for other areas. Program development is done by another group, which coordinates input from regional infrastructure managers. The development of AIT's infrastructure management information system is the responsibility of another group. There are about seven staff members in the highway asset management section, 12 in program development and delivery, and nine regional infrastructure managers and engineers (in four regions).
As noted earlier, AIT outsources much of its activities, including maintenance functions. These contracts define the types of work activities that are to occur via contract activities and establish desired outcomes of such contracts, but AIT does not specify how to produce these outcomes.
One of the important distinctions between the Canadian and U.S. transportation systems is that highway projects in the provinces are funded almost entirely by the provincial government. Therefore, highway budgets compete with other infrastructure (e.g., schools and hospitals) as well as other budgetary priorities.
In 1997, the provincial government recommended that a more coordinated capital planning process be put in place to determine the best investment among competing demands. A Capital Planning Initiative (CPI) was included in the 1999 government business plan to “ensure effective and innovative capital planning and funding of government-owned and supported infrastructure.” Thirteen governmental ministries participate on a CPI committee, chaired by the deputy minister for infrastructure and transportation. Two of the first goals of this initiative were to develop a provincial strategy for alternative capital project delivery (e.g., public-private partnerships) and to eliminate the maintenance backlog on the province's infrastructure. CPI also monitors trends on common (cross-asset types) performance measures, uses infrastructure management systems to determine the status and predicted performance of the province's infrastructure, reports on the ministries' statements of intent as their actions relate to performance measures, and identifies cross-government capital needs and priorities. The management systems include one for transportation (see below), but also systems for buildings and lands, water management, collections and exhibits, and municipal infrastructure.
The ministries submit a 10-year capital requirements plan and identify 3- and 5-year capital plan alternatives. These alternatives reflect ongoing preservation requirements, plans to eliminate maintenance backlogs, and major new capital priorities and other capital needs. Tradeoffs are determined among different asset investments based on criteria that relate to a ministry's ability to deliver the program, expected performance, economic benefits, cost avoidance, cost effectiveness, and strategic alignment with the government's priorities. Flexibility exists to move funds from one infrastructure category to another. An AIT official noted that the existence of a credible infrastructure management system has allowed AIT to “fight the fight” for increased transport funding.
Performance measures are used by political leaders at the business plan level, by senior department executives to justify budgets, and by operations staff to identify potential work activities. Three categories of infrastructure performance are used for all asset types (including those outside the transportation sector) to measure current and future performance. These performance measures relate to condition, use, and functional adequacy. For condition, AIT rates pavement roughness as good, fair, or poor using the International Roughness Index (IRI) averaged over 1-km sections. The condition measure is differentiated by road type: roads with speeds greater than 110 kilometers per hour (km/h) (68 miles per hour (mi/h)) or less than 110 km/h. “Poor” is defined as 1.9 m/km for 110 km/h roads, and 2.1 m/km for less than 110 km/h roads. Use is measured as the percent of road kilometers at service level C or better. Functional adequacy is determined as the percentage of kilometers that meet width standards, horizontal alignment standards, and appropriate road surface type for traffic volume levels, and that have no weight restrictions.
AIT has no difficulty reporting those sections of its highway network in poor condition. An AIT official noted that actually reporting on poor road sections represents a change in agency philosophy because 10 years ago this condition level would have been downplayed. Now, it is used to justify funding requests.
“You can't do anything without performance measures.”
— AIT official
The 2005-2008 Business Plan for Alberta Transportation identified several performance measures considered important in achieving progress in the agency's core business areas. The asset management-related measures included the following:[19]
| Performance Measure | Last Actual 2003-04 | Target 2005-06 | Target 2006-07 | Target 2007-08 |
|---|---|---|---|---|
Physical condition of highways |
||||
% in good condition |
65.5 |
62.0 |
58.5 |
56.0 |
% in fair condition |
23.3 |
24.0 |
25.0 |
25.5 |
% in poor condition |
11.2 |
14.0 |
16.5 |
18.5 |
Use of provincial highways |
||||
% highways that accommodate current volumes at required LOS |
99.9 |
99.0 |
99.0 |
99.0 |
Functional adequacy of highways |
||||
% of highways not subject to weight restrictions and meeting current engineering standards |
80.1 |
79.8 |
79.7 |
79.6 |
Provincial highway paving |
||||
remaining kilometers of graveled provincial highways to be paved |
630 |
560 |
500 |
430 |
Construction progress on North- South Trade Corridor |
||||
% of four-lane road open to traffic |
82.0 |
84.0 |
89.0 |
90.0 |
Ring roads in Edmonton and Calgary |
||||
% of ring roads open to traffic |
18.2 |
18.2 |
26.5 |
40.0 |
AIT began developing its transportation infrastructure management system (TIMS) in 1996. By 2006, TIMS will consist of a suite of 20 software applications that cover such highway assets as bridges, roads, culverts, signs, signals, and other associated structures and appurtenances. TIMS is expected to integrate the different databases, allowing AIT to optimize program delivery. AIT officials estimate that even if only 20 percent of AIT staff use the finished system, it will have paid for itself. When done, TIMS will cover about one-third of all the province's assets. AIT officials noted the following system benefits:
The data included in TIMS are referenced to a common datum; highway attribute data are referenced to a common network. Data are collected using geographic coordinates and reported using linear referencing. The provincial highway system, municipal road network, and bridges are included in the TIMS databases. Every AIT employee with access to a computer can use TIMS for a variety of purposes, including appurtenance inventory, bridge condition information, network expansion projects, a routing and permitting system, performance measurement, and quality assurance of data collection.
TIMS consists of several core components (see figure 13), including the following:
Network Expansion Support System (NESS)—NESS is a decision support system that uses expert opinion and objective information to define current and future conditions of the road network. It acts as an expert system by identifying work activities necessary to deal with identified problems. Each highway section is rated from a technical (level of service and geometrics), safety (collision rates), and socioeconomic policy perspective. The degree to which each of the first two criteria deviate from the norm for the type of road being investigated is used to assess the level of problem experienced at that location. Different types of work activities—data collection, engineering analysis, and rehabilitation/capital improvement—are assigned to each section of road where problems exist or are likely to exist in the future. Figure 14 shows the concept of how different technical, safety, or socioeconomic factors can identify a section of roadway as a candidate for improvement. The horizontal bars represent locations along a highway where these factors need to be addressed, and the cumulative bar at the bottom suggests where multiple work activities need to occur along this stretch of road.
Bridge Expert Analysis and Decision Support (BEADS) System—This prototype system examines different bridge strategies, combined over the entire bridge network, to facilitate short-term programming (3 to 5 years), analyze long-range budget scenarios (longer than 5 years), evaluate status of the bridge network, and assess impact of policy decisions.
Figure 13.Core work processes in TIMS in Alberta.
Figure 14.Buildup of candidate improvement road sections in Alberta.
BEADS consists of three modules: condition, function, and a strategy builder. The condition-related measures reflect the condition of the superstructure, paint, and culverts (see figure 15). The function-related measures reflect width, strength or load capacity, vertical clearance, and existence of bridge rail. Both modules include triggers that relate to work activities required at specific times in the life cycle of the bridge. Deterioration models are incorporated into the module aimed at a 65-year deterioration range. Interestingly, the function module also calculates the user costs associated with not completing possible work actions.
The strategy builder module is the most important module in BEADS. This module assembles life cycle strategies based on input from each module, and compares a large number of strategies on a life cycle economic basis. Two base strategies—“do nothing then replace” and “do nothing then close”—are considered for each bridge. Up to 13 additional base strategies can be developed, each assuming replacement in a future 5-year increment from the previous base strategy (e.g., replace in year 10, replace in year 15, etc.). The module uses a least-cost net present value (NPV) action plan from the condition modules, and keeps track of the cost of actions up to the replacement year and the user costs for functional deficiencies. The results of the strategy builder module include a list of ranked strategies for each bridge structure, a recommendation of a least- cost NPV strategy, a point of departure for an expert review by bridge staff, and a statement of need for additional inspection, assessment, and review of the bridge structure.
Figure 15.BEADS components in Alberta.
Highway Pavement Management Application (HPMA)—This management system is similar to those used in the United States. It consists of an inventory of pavement assets, including pavement condition (current and historical data), an estimate of current and future network deficiencies and needs, the selection of maintenance and rehabilitation treatments, an economic assessment, and the selection of an optimal program of investment. HPMA provides visual representation of layer thickness, width, and material for both longitudinal and lateral sections on a roadway, and a record of the maintenance and rehabilitation activity on the pavement. It also represents visually the pavement surface type, International Roughness Index (IRI), distress index (SDI), structural adequacy index (SAI—deflection), and traffic data. Triggers are used in the IRI, SDI, and pavement quality index (PQI) measures to recommend short-term treatments, whereas prediction models are used to determine performance trends. Decision trees are used to select maintenance and rehabilitation treatments based on current and future conditions. The HPMA also allows the user to define a 5-, 10- and 20-year investment program, either to maintain certain condition levels or to meet budget constraints.
Data collected by AIT support the TIMS system and appurtenance inventory, are used in mapmaking, provide input into highway surface and geometric design, identify crash characteristics, feed into performance measurement, and support truck routing and permitting. Transverse paved-surface characteristics, vertical and horizontal geometry, line painting location and type, and location of appurtenances are obtained from video log data. AIT has embarked on a 3-year project (2002 to 2005) to collect base data on the provincial highway system on all driving lanes in each direction, which will be maintained over time with a slightly reduced coverage (e.g., IRI/rut collected in the driving lane in one direction, digital video logs made in only the driving lane in both directions, and new data collected only on roads that have significantly changed status).
The data-collection program for IRI and rut data has been given to a private contractor, with strong management guidance from AIT. According to AIT officials, the key factor for success of this data-collection model has been applying quality assurance (Q/A) protocols. Ten Q/A sites were established jointly by AIT and the data-collection vendor: two IRI/rut calibration sites, traversed at the start and end of the collection season; six 500-m IRI/rut/geometric verification sites; and two 1,000-m IRI/rut/geometric verification sites. Twenty global positioning system (GPS) blind sites were established at locations unknown to the vendor. AIT used these blind sites to assess the quality of the data collection after delivery. For IRI accuracy, known sites had to be traversed once every 3,000 km/7 days (1,864 mi/7 days) and results submitted to AIT immediately for approval. The GPS location measured at these sites had to be within 2.00 m (2 yd) in the x, y directions and 1.75 m (1.9 yd) in the z direction 90 percent of the time. The IRI/rut values had to be within 10 percent of the actual IRI values plus 3 millimeters (mm) (0.12 inch (in)) for ruts of known values. The Q/A of video logs was related to established criteria for acceptance (e.g., bug splats, rain, and sun angle), with video data delivered every 30 days for review. Appurtenances are spot checked against ground truth locations where data has already been collected.
The various types of data have different schedules. For example, the IRI and rut data are collected annually on the entire network. Surface distress data, collected by AIT staff, are collected on a cyclical basis with 50 percent of the network collected each year. The schedule for bridge inspection data depends on different classifications of highway. All bridge inspections are also outsourced. Data entry is done by the data collectors and verified by department staff. The cycles defined for Level 1 (or routine) inspections are based on structure type and roadway type, and include the following:
Level 2 (or condition) inspections require specialized equipment or expertise and are determined as a result of information from Level 1 inspections. The department's estimated annual costs for data collection include the following:
These costs total Can$26 per lane-kilometer (US$33.50 per lane-mile) with video and Can$19 per lane-kilometer (US$24.50 per lane-mile) without video.
AIT uses scenario analysis to examine the implications of different investment strategies on the performance of the highway network. Typical scenarios include the following: What level of funding is necessary to maintain current performance? What happens if current budget levels are applied in future years? What happens with different investment budgets? To determine future road performance at the network level, it is assumed that the network deteriorates at a 5 percent per annum rate. AIT's business plan is based on this analysis.
Life cycle cost analysis is used throughout the asset management program. For individual projects, pavement life span is determined as the time it takes pavement quality as measured by the Pavement Quality Index (PQI) curve to reach a trigger level (e.g., PQI = 6.5 on a 0-to-10 scale). The life cycle will typically include two or three of these life spans, corresponding to an analysis period of 50 years. Remaining service life is not calculated as part of the assessment. Bridge engineering uses a 50-year life with a 4 percent rate of return for life cycle analysis. As part of the life cycle analysis for bridges, a remaining service life is calculated and modified by condition data obtained from inspections.
Although AIT does not now use benefit-cost analyses to establish project priorities in program development, it is developing such an optimization module for TIMS. AIT officials now use a ranking system based on condition data and other factors as a guide in program development. The output from this ranking system is reviewed and adjusted by regional infrastructure staff.
The development and use of a cross-asset comparison and prioritization scheme was an interesting aspect of the Alberta case. The CPI committee set up a task group to identify a process for prioritizing among different asset types with a focus on capital projects. The resulting rating system assigns points to projects to the extent they help achieve government policies and meet program delivery criteria relating to condition, use, and functionality. A project can receive a maximum score of 100 points. Departments are responsible for prescreening projects before they are rated to confirm 1) the project's need, scope, and cost; 2) the proponent's ability to implement the project; and 3) that the project is a high priority for the agency. According to the prioritization guidelines, the points are assigned in the following way:[20]
This category assesses condition, utilization, and functionality restraints on program delivery outputs according to optimal and basic program delivery standards established by departments. It considers how seriously these standards will be compromised if the project does not proceed.
The rating system assumes all government programs (schools, hospitals, museums, etc.) are of equal priority and gives equal weight to all programs. Program Delivery is rated according to the intrinsic requirements of each program. Up to 72 points.
Where projects address health and safety hazards caused by the infrastructure itself, the system provides for increased points under the Health and Safety category. Up to 4 additional points.
Three factors provide additional points based on economic considerations, representing 24 percent of the maximum potential rating score.
The Economic Benefit Factor is based on four key objectives of the Province's economic strategy. Up to 12 additional points.
The Cost Avoidance and Savings factor awards points to projects that will result in future savings to the province or provincially funded agencies based on program delivery or facility operation and maintenance costs that will be saved if the project is implemented. Up to 8 additional points.
The Value and Cost Effectiveness factor awards points where the capital cost funding commitment is less than indicated by provincial guidelines, usually because of funding from others (public-private partnership arrangements, fund raising, other governments, etc.). Up to 4 additional points.
Maximum Score: 100 points
AIT has made a major commitment to asset management as part of its business plan and as a key component of its role as a road manager. AIT was the only state-level agency the scan team visited where officials were responsible for more than road assets. Thus, the way tradeoffs occur among asset categories was an interesting aspect of this case.
Several important characteristics of the asset management approach at AIT stand out. It is very clear that high-level managers have bought into the asset management approach to network stewardship. In many ways, the entire organization has been reinvented to incorporate a different business and decisionmaking culture. Asset management is viewed as an important means of determining the best business decision for a large portion of the agency's budget. AIT's credibility with other agencies, the public, and, perhaps most importantly, the elected government is strongly tied to having a defensible and understandable technical foundation underlying its recommendations.
Another aspect of asset management in terms of the buy-in was the need for such a strategic perspective in an environment where much of the service delivery is outsourced. AIT has learned that outsourcing such services requires a more active role by the asset owner to make sure the right things are being done.
AIT is developing a state-of-the-art infrastructure management system. The many different modules and their roles in supporting agency decisionmaking were impressive. Once this system is completed, it could very well be at the leading edge of decision-support systems at state-level transportation departments. The use of a locational referencing system to tie databases together is also a useful model for other agencies. The BEADS and NESS functionalities were particularly impressive.
The use of TIMS to build up work activities (see figure 13) is a very important and useful capability. Once this entire system is in place and functioning, TIMS will likely become a critical tool for AIT in responding to asset deficiencies quickly and efficiently.
For cross-asset category comparisons, the use of similar performance measures—condition, use, and functionality—across infrastructure groups allows AIT officials to develop a best-value investment package. The scoring scheme developed for the CPI process is an innovative attempt to examine cross-asset prioritization. Although models and analytical procedures to provide a dollar-for-dollar comparison across these asset categories do not appear to be in place, tradeoffs are likely to occur and information from systems like TIMS can be critical in supporting the transportation asset portion of this comparison.
One of AIT's goals is to become a center of excellence for transportation in North America. At least in the asset management arena, it appears to be well positioned to become exactly that.
[19] Alberta Infrastructure and Transportation, Business Plan, 2005-2008, April 13, 2005, see http://www.finance.gov.ab.ca/publications/budget/budget2005/inftra.html#7.
[20] Capital Planning Initiative, 2003-2003, Government of Alberta,
