IMPLEMENTATION OF IMPROVED PROCESS FOR DEVELOPING ...

4th International Conference on Managing Pavements (1998)

IMPLEMENTATION OF IMPROVED PROCESS FOR DEVELOPING LONG-RANGE PAVEMENT REHABILITATION PROGRAMS 1

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Li Wang, Michael I. Darter , Kathleen T. Hall , Yan Lu , David L. Lippert

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Consultant 12075 Oxbow Drive, Minneapolis, MN 55347, US 1

ERES Consultants, Inc. 505 W. University Ave. Champaign, IL 61820-3915, US

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Consultant 603 Teal Cove Champaign, IL 61820, US

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ERES Consultants, Inc. 505 W. University Ave. Champaign, IL 61820-3915, US

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Illinois Department of Transportation 126 E. Ash St. Springfield, IL 62704-4766,US

Abstract The major deficiencies existing in current long-term rehabilitation program generation has been identified. An improved methodology that takes advantage of both the analytical and manual methods is introduced. A software package developed based on this improved methodology is presented. Applications of this improved methodology are explained through several scenarios. The conclusion is drawn as this improved methodology can generate both practical and cost-effective multi-year rehabilitation plan through fast data assessment, comprehensive network health evaluation, a multi-algorithm generator, and human-computer interaction.

INTRODUCTION The two main methodologies used by highway agencies in the development of a long-range rehabilitation program are the manual method and the analytical method. The major deficiency of the program generated by the manual method is that it is practical but not cost-effective, due to the lack of comparing potential cost/benefit tradeoffs among different alternatives. The major deficiency of the program generated by an analytical method is cost-effective, but not very practical due to oversimplification of the real problem. Using a mathematical model is not adequate because engineers and managers are not involved in the decision-making process. In reality, a good long-range rehabilitation program must be both cost-effective and practical. This major deficiency has caused

TRB Committee AFD10 on Pavement Management Systems is providing the information contained herein for use by individual practitioners in state and local transportation agencies, researchers in academic institutions, and other members of the transportation research community. The information in this paper was taken directly from the submission of the author(s).


agency difficulties in accepting either the manual or analytical pavement management system (PMS) for many years. In order to overcome this deficiency, a new methodology was developed making use of both the manual and analytical method advantages in developing a long-range program. The new concepts are first a graphical data interpretation and the use of "visual thinking." Second, pavement performance evaluation should be comprehensive and quickly accessible. Third, human knowledge should be involved in the decision-making process through a user-friendly interface. Finally, the process should be repeated until an acceptable rehabilitation program is reached. Seven basic components should be included in any PMS (Wang et al, 1997). • • • • • • •

Data collection, storage and retrieval Pavement condition assessment Flexible program generator Performance evaluation process Program adjustment Pavement network quality evaluation and comparison Final program generation TM

A graphical/interactive and Windows -based pavement management system called Windows ILLINET was developed based on both the new concepts and methodology. It TM can be utilized under Microsoft Windows on a personal computer. This system is being used by the Illinois Department of Transportation personnel in development of long-range rehabilitation programming (Wang et al, IHR 529, 1995). In order to satisfy Intermodal Surface Transportation Efficiency Act (ISTEA) regulations, (Federal Highway Administration, 1989) all State agencies are required to develop longrange pavement rehabilitation programs. However, for different agencies and levels of management, the degree of detailed information required is different. Furthermore, the PMS outputs they would want to obtain are diverse. As far as pavement engineers are concerned, a PMS should be able to answer all questions about the network pavement condition, future condition, and rehabilitation strategies. Scenarios that State agency pavement managers encounter frequently in developing a long-rang rehabilitation program are presented in Figure 1, and are discussed in the following sections.

EDIT INVENTORY AND SYSTEM INFORMATION The district pavement managers can update the database through ILLINET for their own district. Windows ILLINET offers several major functions including editing both inventory and system control parameters as shown in Figure 2.



Figure 1. Applications of new methodology

Edit inventory information Before using any other system function, the pavement manager needs to ensure that the database is correct and current. If not, the function "Edit Data Base" on the main menu should be used for editing purposes. The information for each pavement section, belonging to a selected district, can then be edited through the four windows as shown in Figure 3. Window (a): Window (b):

allows section selection from the map or list. allows section information modification in the userfriendly interface. Windows (c) and (d):allows a section to be split into two, and the data then modified.



Figure 2. Main functions of ILLNET

Confirm system parameters Before running any system algorithms, the pavement manager needs to confirm whether the system control parameters and criteria are as desired by using the function, "Edit Parameters." Figure 4 shows all eight groups of editable control parameters used in this system: (1) (2) (3) (4) (5)

Condition Rating Survey (CRS) parameters: The coefficients for the pavement condition deterioration curve for each pavement family. Decision Tree Cutoffs: The decision tree matrix for selecting the project-level rehabilitation strategies. Unit Cost: The unit cost for four rehabilitation types and six pavement families. Adjustment Factors: The factors used to adjust the rate of pavement deterioration. System Defaults: The defaults for inflation, traffic growth rates, and maximum pavement remaining life used in the calculation of long-term benefits.



Figure 3. Inventory data editing (6) (7)

(8)

Trigger Values: The triggers for calculating the remaining life, and for defining what is "Adequate," "Accruing," "Backlog," and "Critical Backlog." Unit Cost Adjustment: The factors used to adjust the unit costs input in item (3) above. When the pavement's CRS is less than 6.0, the rehabilitation construction costs will be higher. Unit User Cost: The average vehicle operating cost for all vehicles in the traffic mix, for different pavement condition levels.

If any parameters are changed, they only affect the District that the pavement manager selected. The other Districts will use either their own or the system default parameters.

IMPROVE AN EXISTING PROGRAM In a State agency, the existing program is updated every year. This requires evaluating the current program and adding new projects for deteriorated sections for an additional year. In addition to updating this existing program, the long-range rehabilitation program generated by "Ranking", "B/C", "IBC" (Wang, 1995) or some other approach also needs improvement in order to be practical and effective.



After a long-range rehabilitation program has been initially generated, many modifications may be needed to make it practical and effective. The program improvement involves: • •

Input of the existing program into Windows ILLINET Evaluate the predicted pavement performance, cost, and benefit of all

Figure 4. System control parameter editing

• • •

sections in the network Assess the current and historical conditions Modify and reevaluate the program Generate the final report

Enter existing plan and predict pavement performance If the program or part thereof is manually developed or predetermined, the first task is input this predetermined program into Windows ILLINET using the program editing window as shown in Figure 5.



Once the program is input, pavement performance, rehabilitation costs and benefits can be evaluated for reasonableness. "Committed Rehab Only" algorithms in "Run Programs," as shown in Figure 6, can be used for predicting the performance based on the current pavement condition, predicted traffic volume, and predetermined rehabilitation decisions using the built-in statistical performance prediction model (Lee, 1993).

Figure 5. Program input and editing Evaluate pavement performance After running the committed algorithm, "Show Output" in the main menu can be used to check the predicted pavement performance, costs, and benefit information as shown in Figure 7. There are five windows showing the network performance, costs, and benefit summaries; one to show overall pavement quality evaluation; three in chart format; and two in map format to show the route performance summary. Detailed data tables and report generation are also included in this function. For example, Figure 8 shows the five network analysis windows and the overall quality evaluation window. Since there is no adequate single indicator of overall pavement infrastructure performance (Board on Infrastructure and the Constructed Environment, National Research Council, 1995), several measurements are used in Windows ILLINET to



demonstrate network health. The overall network quality is measured by a composite indicator called Pavement Health Index (PHI). It can be combined by any of the measurements with desired weights (Wang et al, IHR 529, 1995). All indicators and the index are presented in a graphical format for easier understanding of the predicted network performance. For example, this figure indicates that from 1995 to 1999, even though the annual network average CRS (from 6.5 to 6.4) does not change significantly, more than 10% of VMT (Vehicle-Mile-Traveled on good pavement), and almost 20% of user cost shifted from Adequate to Critical Backlog. The remaining life range for 90% of the sections is the same at 6.5, and the average life reduces from year to year. The overall pavement quality is relatively low as shown on Figure 8(f), with WeightVMT=40, WeightLife=40, and WeightCRS=20.

Figure 6. Running pavement performance prediction and analysis



Figure 7. Output review options In order to decide if some section should be rehabilitated earlier or use another rehabilitation strategy, the rehabilitation history and traffic data should be assessed as discussed below. Assessment of the current and historical conditions More current and historical information on pavement sections can assist managers in making better informed rehabilitation decisions. Since more and more data are collect and stored, visual data interpretation becomes the best vehicle to access the larger databases (Wang et al, 1995). Figure 9(a) shows the "View Pavement Information" window that contains four options, CRS, Traffic, Rehab history, and digitized video images. Once a section is selected, the past and predicted CRS can be displayed in graph (c); the rehabilitation history and layer information is in (b); and the traffic history is in graphs (d) and (b). The relationship between traffic and the pavement capacity is shown at lower left section of (c); that is if the traffic volume exceeds the capacity, the arrow tail will be wider than the pavement surface. All deficient sections should be evaluated one by one to ensure that the decisions are the



most cost-effective. The rehabilitation decisions will then be made based on this evaluation, followed by the predicted performance analysis. Decisions based on practicality or political reasons should also be analyzed. For instance, it is practical to rehabilitate several sections that are close to each other, even with only slightly varying conditions in the same year, to form and better manage construction projects. Generate final program Some rehabilitation decisions may need to be modified through the "Edit Committed Rehab" window shown in Figure 5 after the performance evaluation and condition assessment. The modified program should then be analyzed again by first predicting the pavement performance, then evaluating the performance as discussed above. In other words, the process of editing, predicting, and evaluating should be repeated again and again until a satisfactory program is obtained. This process is interactive between computer and humans. It allows manager involvement in the decision-making process through input their experience and knowledge.

Figure 8. Network analysis After pavement manager is satisfied that all decisions have been made in the long-range rehabilitation program, a final program should be generated and printed along with the corresponding graphs, and then circulated among other engineers and managers.



GENERATE THE PROJECT PRIORITY LIST As a helpful decision-making tool, a PMS should provide useful information on a flexible and interactive basis, i.e., open the "Black Box" of the mathematical algorithms. The "Decision Guide" function offered in this system provides information about project priorities and comparison of the different treatments effectiveness. It tells HOW and WHY a rehabilitation strategy is chosen by the mathematical algorithm, and also allows a pavement manager to analyze and evaluate the information. This application involves the following steps: • selecting the desired algorithms; • running these algorithms, showing the priority lists; • evaluating the priority list, determining the rehabilitation projects; • repeat the above steps for each year; and finally, • developing a long-range rehabilitation program manually based on a combination of the provided information and human's knowledge. Select algorithms For a chosen year, up to four alternative algorithms can be selected simultaneously for analysis and comparison. Figure 10, "Choose Algorithms" window, shows a total of eight network-level algorithms, six project-level strategies, and three benefit options provided in this system. The algorithms with "+Committed Rehab" allow the predetermined projects to be considered in the analysis. Any combination of these three category options composes an algorithm. In this example, four algorithms are selected and shown in the "Selected Algorithms" window. (1)"Rank Only" + "Decision Tree" + "CRS Area": Project-level strategies are selected based on the decision tree cutoffs. The network-level priority is ranked by the predicted CRS in the worst-first order. (2)"Rank + Committed Rehab(dist7.cm1)" + "3-in Overlay" + "VMT": The committed projects are ranked on the highest priorities. The other priority is ranked by the predicted CRS. 3-in overlays are applied whenever the section's condition deteriorates below the rehabilitation trigger value (Min CRS). (3)"B/C Only" + "Life-Cycle Cost" + "CRS Area": The project-level strategies are selected based on the ratios of the cost to the predicted life for the four different options (patching, 3-in overlay, 5-in overlay, and reconstruction). The lowest one will be suggested as the rehabilitation treatment for that section. Then, the long-term benefit which is the area under the pavement condition CRS curve, is calculated for the suggested treatment of all deficient sections. After that, the ratio of the benefit to the cost (B/C) for the suggested treatment for all deficient sections is calculated and ranked at the network level in descending order. (4)"I B/C Only" + "VMT": The long-term benefits, the costs, and the ratios of the benefit to the cost of all four project-level rehabilitation treatments for all deficient sections, are calculated and



Figure 9. Condition assessment ranked together. In this example, the long-term benefit is Vehicle-Miles Traveled on the Adequate pavement condition during the pavement life. Generate and display priority lists After selecting the desired algorithms, the pavement performance, costs, and benefit for each pavement project can be predicted and the priority lists can be generated by pressing "Run" in the "Decision Guide" window as shown at the top of Figure 11. The Priority lists are generated and displayed in certain formats depending on the different algorithms selected as shown in Figure 11. Basically, the lists show Section ID, Rank, Suggestion and Cost. For IB/C algorithm, there is only one level of Rank, while the others have Network Level and Project Level Rank.

Develop a rehabilitation program The priority lists give more accurate information on comparison among different alternatives. This information can be combined with a manager's experience and



knowledge to help in making rehabilitation decisions. Once the decision has been made, the program can be edited in the "Edit Decision Plan" window, as shown in Figure 5, on a yearly basis.

Figure 10. Algorithm options in Decision Guide



Figure 11 Priority list display in Decision guide DEVELOP A REHABILITATION PROGRAM BASED ON NEEDS ANALYSIS This involves estimating budget requirements needed to preserve the pavement network at acceptable levels of performance (minimum standards). The budget in this type of analysis is assumed to be unlimited. Basically, the program tells where, when, and what type of rehabilitation strategy should be applied to maintain the pavement condition above a certain level. The benefits obtained at increasing levels of investment funding would be useful knowledge as compared to the full needs funding (which is usually impractical and may not even be effective from a cost-benefit standpoint). The steps involved in developing the Needs program are: (1) (2) (3) (4)

Enter predetermined projects as committed projects, if applicable. Select the network-level analysis algorithms as "Needs + Committed Rehab" or "Needs Only" depending if any committed projects need to be considered. Select a project-level strategy from "Decision Tree", "Life-Cycle Cost", and "Single Rehab". Choose benefit. One of the three long-term benefit options should also be selected for demonstrating performance analysis purposes. However, this benefit option is not a decision-making factor in the "Needs" algorithm. It is used only for showing the long-term



(5)

benefit performance indicator. Generate the program and improve it as described in the previous sections.

DEVELOP A REHABILITATION PROGRAM WITH BUDGET LIMITATIONS This is the most common work for pavement managers. Every year the pavement managers are required to develop long-range rehabilitation programs based on limited funding. This application involves selecting the desired algorithm, generating the initial long-range rehabilitation program based on the pavement performance prediction and budget restraints, and improving the generated program. Development of a rehabilitation program with the highest benefits for the given cost is attractive to all pavement managers. Mathematical methods have many advantages in accomplishing this goal. However, the disadvantage is that it is currently impossible to make the results practical and therefore satisfy the managers. The best way to solve this problem is to combine the mathematical method with the pavement manager's knowledge to reach a practical and optimal solution. Hence, this program development process involves: • Input of predetermined projects • Select desired algorithms to generate an initial program under budget constraints • Predict the pavement performance, rehabilitation costs, and the benefits to be obtained from the rehabilitation • Evaluate and improve the program by checking the practicality and the pavement performance. • Repeat the process of prediction, evaluation and improvement until reaching a final satisfactory program. Select desired algorithm Selecting a desired algorithm to generate the initial program is critical in this process. As mentioned before, there are many combined algorithms to choose from. The following are some suggestions on how to select an algorithm to achieve the desired goals. Network-Level: (1) When concerned with long-term benefit and cost in looking for a cost-effective program, the pavement manager may want to choose from either of the following to generate the initial program. "B/C" -ranks the long-term benefit/cost ratios over the pavement life after rehabilitation. Selects the best ones until the budget is exhausted. "I B/C" -ranks the incremental long-term benefit/cost ratios (_B/_C) for all possible treatments and all deficient sections. Selects the best ones until the budget is exhausted. (2) When concerned with the current pavement condition, the pavement manager may want to choose the "Ranking"-- ranks the yearly predicted CRS, selects the worst ones until the budget runs out to generate the initial program. The situation visualizes the manager in any future year with all pavement conditions known, where he or she allocates the budget in that year based on the worst-first principle without considering the next few years.



Project-Level: (1) When concerned with project cost-effectiveness, the pavement manager may want to use: "Life-Cycle Cost"-- ranks the ratios of costs to the remaining lives for all possible treatments, the lowest one will be selected; (2) To facilitate the process of understanding and implementing, the manager can use either of the following strategies that already merges a great deal of previous experiences: "Decision Tree" -- gives the pavement condition ranges as the project selection cutoffs; "Single Rehab" -- gives the treatment suggestion. Benefit Option: (1) In a heavy traffic network, traffic consideration dominates the rehabilitation strategy selections. In this case, the pavement manager may want to use: "VMT" -long-term benefit considering total vehicle-traveled on smooth pavement over pavement life; "User Cost" -- long-term benefit considering total money that will be wasted for not traveling on smooth pavement. (2) If the manager would like to consider the overall pavement condition without considering the traffic volume, he or she may want to choose: "CRS Area" --long-term benefit considering the total areas under the pavement condition curves. SUMMARY Through all application scenarios, it is noticed that the improved methodology can remedy the major deficiencies in the current process of developing the long-range rehabilitation program. As mentioned in the introduction, the current method develops the program using either the manual method (which does not allow ease in comparison and evaluation among the various generated programs), or using the mathematical method (typically not practical). The improved methodology makes use of advantages from both the manual and the mathematical methods, allowing the pavement manager to develop a more cost-effective and practical rehabilitation program using human-computer interaction and multi-media techniques. REFERENCES Wang, L., M. I. Darter, K. T. Hall, and Y. Lu, D. L. Lippert, 1997. Improved Methodology for Developing a Long-Range Pavement Rehabilitation Program. Presented at January 1997 Annual Meeting of Transportation Research Board, accepted for publication in Transportation Research Record. Wang, L., Lu, Y., Darter, M. I., Hall, K.T., Lippert, D.L., IHR 529, 1995. Development, Evaluation And Improvement Of A Long-Range Pavement Rehabilitation Program. Illinois Highway Research Project IHR 529, University of Illinois and Illinois Department of Transportation. Federal Highway Administration, 1989. Federal-Aid Highway Program Manual. Volume 6, Engineering and Traffic Operations, Chapter 2, Standards and Design, Section 4, Pavement Management and Design, Subsection 1, Pavement Management and Design Policy.



Wang, L., 1995. Development, Evaluation and Improvement of a Long-Range Pavement Rehabilitation Program. Ph.D. thesis, Department of Civil Engineering University of Illinois at Urbana-Champaign. Lee, Y., 1993, Development of Pavement Prediction Models. Ph.D. thesis, Department of Civil Engineering, University of Illinois. Board on Infrastructure and the Constructed Environment, National Research Council, 1995. Measuring and Improving Infrastructure Performance National Academy Press, Washington, D.C. Wang, L., Lu, Y., Darter, M. I., Hall, K.T., Lippert, D.L., 1995. An Interactive / Graphical Pavement Management System. Transportation Research Record 1508.

KEYWORDS Pavement Management, Interactive / Graphical System, Pavement Performance Evaluation, Rehabilitation, Infrastructure


IMPLEMENTATION OF IMPROVED PROCESS FOR DEVELOPING ...

IMPLEMENTATION OF IMPROVED PROCESS FOR DEVELOPING ...

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