Enhancement of Pavement Maintenance Management Using GIS

Abstract

In pavement maintenance management, it is beneficial for engineers and planners to spatially visualize and analyze pavement maintenance information so that the pavement maintenance resources can be allocated reasonably. The pavement maintenance information includes pavement condition rating, distress distribution and the required rehabilitation. Geographic Information System (GIS) provides an excellent spatial query and analysis capability. With these capabilities, the pavement maintenance management can be greatly enhanced. This study uses an Esri product, ArcviewTM to analyze the pavement condition survey data provided by Georgia Department of Transportation (GDOT) for Gordon Country, Georgia. This study focuses not only on the application of GIS on pavement maintenance management but also on how transform data from different data formats into the GIS environment. An assumption about segment rating mainly caused by load cracking was made. Hypothetical data about associated rehabilitation methods and costs were also used to demonstrate the full functionality that can be provided through using GIS. Two visualization alternatives upon levels of detail about information are presented in this paper. One is route-level, based on line, and the other is county-level, based on polygon. The spatial distribution about the pavement rating can be displayed and subsequently the associated rehabilitation methods and costs can be then analyzed.

Introduction

Georgia Department of Transportation (GDOT) uses the Pavement Condition Evaluation System (PACES) for the consistent field survey work in the whole state. The PACES survey is done on the project level. The project rating ranges from 0 to 100. The projects with a rating less than 70 need to be further investigated to determine the need of treatments. The associated rehabilitation cost can then be analyzed. This study focuses not only on the application of GIS to pavement maintenance management but also on how to transform data from different data formats into a GIS environment. PACES data and spatial data in Gordon Country, Georgia for the past 10 years were used in this study. An assumption about segment rating mainly caused by load cracking was made in this study. Hypothetical data about associated rehabilitation methods and costs were also used to demonstrate the full functionality that can be provided by GIS. Two visualization alternatives depending upon degrees of information detail and offering different advantages are presented in this paper. One is to display the spatial distribution about the pavement rating and subsequently to analyze the associated rehabilitation methods and costs for the entire county. The other is to display the spatial distribution about pavement rating for a selected route and the segment ratings on the route can be displayed continuously on a chart. The detailed surveying result for each segment can be easily extracted from the chart, along with a photo taken in the field.

Data Sources and Assumptions

The following data are provided by GDOT:

(1) Spatial data for Gordon County:

Spatial data include Gordon County boundary, city boundaries within Gordon County, and the routes in Gordon County. The boundaries of Gordon County and city boundaries are defined as polygons. Routes are defined as lines and are divided into segments. Typically each segment is one mile, unless the road conditions change, the segment less than one mile is used. Each route has a unique ID, RCLINK, which is a 10 character string combined by three digit county number, one digit route type, four digit route number, and two digit route suffix type as defined in [1]. For example, a state route with route type 1 in Gordon County with county number 129, and a route number 201 and suffix code 00, the RCLINK for this route would be defined as 1291020100. Each segment has the basic information of a beginning point and an end point with the RCLINK.

(2) Pavement Condition Evaluation Data:

PACES (Pavement Condition Evaluation System) is a manual for the field survey work developed by Georgia Department of Transportation (GDOT), which is used as the basis for the entire fieldwork so that the survey data can be consistent within the whole state. The PACES survey is done on the project level. A route may be just a project, or may be divided into several projects. A project then is divided into several segments usually based on the milepost. For each segment, a survey is done on the selected 100-foot long pavement section where the most severe distresses are exposed. On this section, each type of distress, as well as the severity level of this type of distress, is recorded based on certain methods specified in PACES manual. After doing these for all the segments within the project, each type of distress is averaged and the deducted value for this type distress is calculated. Finally, the project rating for this project is calculated based on these deducted values. For details, please refer to PACES manual [2]. PACES data include the project information as well as the segment survey data.

The project information contains the project location, the route number, the county number, the route type, the beginning point, the end points, the project limits, and the length of the project. The pavement information includes the surface type, the traffic information, the pavement width, the shoulder width, and the number of bridges. The project rating, including the percent of distress and its severity level, the deducted value of this type distress, and the project distress rating. The detailed PACES survey data is shown in Table 1.

Table 1 PACES Field Survey Data Sample

(3) Unit cost for Rehabilitation Method

Assumptions about segment rating mainly caused by load cracking and the associated rehabilitation methods and cost were used in this study in order to demonstrate the full functionality that GIS can provide for pavement maintenance management. The associated rehabilitation methods were categorized based on segment ratings as shown in Table 2 because the load cracking was assumed to be the major cause. The associated unit cost for each rehabilitation method was assumed as shown in Table 2.

Table 2 Rehabilitation Method and Unit Cost with Respect to Range of Segment Rating

Data Transformation

With GIS capability, pavement maintenance information can be visualized and analyzed spatially based on different jurisdiction such as city boundary, county boundary, state boundary, working district, as well as congressional district. Two visualization alternatives upon degrees of information detail are presented in this paper. One is to display the spatial distribution about the pavement rating and subsequently to analyze the associated rehabilitation methods and costs for the entire county. The other is to display the spatial distribution about pavement rating for a selected route, and the segment ratings on the route can be displayed continuously on a chart. The detailed surveying result for each segment can be easily extracted from the chart with a photo taken in the field. Two alternatives of the GIS applications are described as follows.

Alternative 1: Route-Level Analysis.

Route ID, 1291040100, was used to select the Interstate I-75 for route analysis and a new theme was generated subsequently. The distress rating for each segment along the Interstate I-75 was displayed with the graduated color method as shown in Figure 1. A field photo was linked with each segment to provide the image about distress conditions as shown in Figure 1. This is especially useful to differentiate segments with the same rating and different distress conditions. Rehabilitation was required for the rating less than 60. The segments requiring rehabilitation can be easily allocated for the current year. Distress development for each route can be visualized by displaying distress ratings along the route for different years as shown in Figure 2. As shown in Figure 2, the detailed information for a specific segment can be easily queried. The variation of the segment ratings for different years can then be analyzed to support the further study. These studies may be the reasoning of the increase in segment rating due to maintenance work or the decrease in segment rating due to material deterioration. Therefore the performance of each rehabilitation method to different distresses can be quantitatively evaluated while integrated with Equivalent Single Axle Load (ESAL) or age. Pavement maintenance information at this route for a specific year, including the distress types, the rehabilitation methods, the total length of routes segment that were rehabilitated, and the cost of the rehabilitation can be analyzed. As shown in Table 3, the rehabilitation cost with the associated rehabilitation method along I-75 can then be summarized.

Figure 1 Distress Rating Distribution Along A Route

Figure 2 Variation of Distress Rating for Different Years

Table 3 Pavement Maintenance Information for I-75 within Gordon County in 1986

Alternative 2: County-Level Analysis.

The distress rating distribution in Gordon County can be visualized for a selected specific year as shown in Figure 3. Images regarding the distress information can be provided through a hot link with a field photo as indicated in the Route-level analysis. The "line-in-polygon" analysis can be used to come up with the total rehabilitation cost in Gordon County for the current year as shown in Table 4. With the distress distribution, the relationship between landuse such as industrial use can be further analyzed, once we incorporate the information from the census tract.

Figure 3 Distress Rating Distrbution in A County

Table 4 Pavement Maintenance Information for All State Routes within Gordon County in 1986

Summary

Acknowledgement

Georgia Department of Transportation is appreciated for the data provided.

Reference