 The Pavement Management System is a tool to assist highway agency managers in decision making. It has three elements, a database, analysis methods, and a feedback process. This program will focus on data collection methods. We'll cover road inventory, pavement condition, traffic data, maintenance, rehabilitation, reconstruction history, and cost data. Road inventory refers to the long-term physical characteristics of each road in a network, not pavement condition. Pavement condition is a separate category for three reasons. First, pavement conditions change frequently as the road ages. Second, road inventory data describes the entire road network. Pavement condition data represents only a sample of each road. Third, train technicians can collect inventory data. But pavement condition data collection often requires special equipment or professional engineering judgment. In order to conduct a road inventory, each road must first have a unique identifier. There are various methods, but most common is a simple numbering scheme. Each road has a unique number. Numbers are easier for computers than names. Most systems use the root number as posted in the field. Some countries and local jurisdictions use a link node approach. Each road intersection is a node. Each road segment between two nodes is a link. Some agencies use the global positioning system, known as GPS, to determine precise locations. GPS equipment uses satellites and triangulation to provide coordinates for latitude, longitude, and elevation. Once a road has a unique identifier, a data collector can precisely locate physical characteristics. They record characteristics such as length, width, thickness, number of lanes, climatic factors, and function. They usually indicate a location using the linear distance along the road's center line from a known reference point to the desired location. Whatever method used, it must be precise, and it must work in conjunction with other systems, like pavement and bridge systems. Road characteristics should be studied in conjunction with other attributes of the road at the same locations. Without this ability, the PMS is useless. The best solution is an agency-wide standard for referencing locations. This allows various data to be related and analyzed for many different purposes. Another category of data is pavement condition. Pavement condition surveys aid in monitoring pavement deterioration. Common indicators are physical distress, ride quality or roughness, and safety. Trained, experienced engineers normally use visual inspection to determine physical distress. They look for three kinds of surface deterioration. Fractures, like cracking or potholes. Distortion, such as swells, depression, corrugation, or rutting. And surface deterioration, like bleeding, oxidation, spalling, polished aggregate, and erosion of the wearing surface. The Strategic Highway Research Program by the United States National Research Council published a distress identification manual for pavements. It has photographs of examples of pavement distress. Evaluation methods vary from windshield surveys to using sophisticated laser equipment. It is unlikely that these devices will ever completely replace visual inspection. Two common physical distress rating methods are a present serviceability index, known as PSI, and a pavement condition rating, known as PCR. The present serviceability index is a mathematical computation based on various field measurements. PSI values range from zero to five. In North America, experts consider values below 2.0 to 2.5 to be the end of the pavement's useful service life. The PCR is similar to the PSI. Its scale goes from zero to 100. Another indicator of pavement condition is ride quality. For many years, engineers have considered ride quality the principal indicator of how well a road is serving the public. Research by the World Bank and other organizations has directly related roughness to increased vehicle operating costs. The closest to a universal standard for measuring roughness is the International Roughness Index, known as IRI. Its units are meters of vertical movement per kilometer. The index is based on a mathematical simulation of a vehicle moving at 80 kilometers per hour. Roughness may indicate serious problems. Spalling, slab failure, depressions, swells and potholes often first cause roughness. Still, these measurements should not be the only pavement evaluation. The early stages of conditions such as alligator cracking may allow smooth, high-speed travel. Engineers measure roughness a number of ways, including roughometers that measure vertical movement between a vehicle's axle and frame, and profilometers that measure the longitudinal profile of the road. Roughometers are very sensitive to operating technique and equipment condition. They are affected by speed of the vehicle, tire pressure, condition of shock absorbers and springs, payload, constant speed and even temperature change. Therefore, operator technique, as well as type and condition of equipment, is very important. At the project level, engineers also measure pavement condition by structural capacity. Structural capacity is the maximum accumulated traffic load pavement can withstand without unacceptable distress. They prefer non-destructive testing to measure structural capacity. Non-destructive testing equipment includes static wheel loading devices, falling weight devices, cyclic dynamic loading devices and newly developed ground penetrating radar that can measure pavement thickness. Some pavement management systems do not require a measurement of structural capacity in the evaluation and prioritization stage of the process. Some systems use ride quality to select deficient pavement. Then, structural capacity analysis is used to determine the appropriate treatment for specific projects. Another condition indicator is safety. Engineers judge safety in two ways, skid resistance and traffic accident data. They define skid resistance as the amount of friction between the road surface and the vehicle tire. In North America, engineers commonly use an ASTM locked wheel trailer or skid trailer to measure friction. It drags a locked wheel across a section of pavement and records friction values. The coefficient of friction or mu value is the towing force divided by wheel load. Values less than 35 are considered hazardous. Another category is traffic data. Engineers use traffic volume and axle load data to evaluate pavement performance, determine priorities and select appropriate treatments. They use mix of traffic as well, including annual average daily traffic and the percentage of cars, trucks of various weight classes and buses. They make traffic counts according to well-established procedures. Axle loading refers to loads on the pavement resulting from traffic volume and a mix of vehicles. It is expressed in terms of equivalent single axle load or ESAL. The net effect of the traffic on the road is expressed as the number of equivalent single axle 80 kN loads. A passenger car represents only a fraction of an ESAL, while a large truck double trailer combination may represent as many as nine ESALs. Road history data is another important category. Most PMS models require information on maintenance, rehabilitation and reconstruction projects. The database should have the date and type of construction plus thickness and type of material. For pavement maintenance, it is not practical to record the type and location of every routine activity. However, it is useful to know the general level of pavement maintenance on each road, on a section by section basis. Abnormal amounts of pavement maintenance may suggest closer scrutiny of the road section. Historical costs of maintenance are the last data category. Engineers use them in the PMS life cycle cost analysis. These costs are not as predictable as construction costs because of the many factors that affect them, such as age and condition of pavement, traffic loads and environmental and climatic conditions. Several years of costs by road section help the model to find trends and make predictions. The model also needs to see if there are decreases in costs after pavement improvements. To run successfully, a pavement management system needs lots of data. That means an agency should have a computer-based relational database management system known as DBMS. There are many DBMS packages for all types of computers, from microcomputers to mainframes. Some PMS programs include a DBMS. Before purchasing a DBMS, agency management should consider the PMS and acquire it. If it does not already incorporate a DBMS, then the agency should get one compatible with the PMS. If the agency already owns a DBMS or has an established policy on the subject, it should check on compatibility with the PMS. Use existing software whenever possible. That avoids support and data exchange problems within the agency. An agency should not forget other databases within the organization. The PMS database will have to interface with planning, design, traffic engineering and maintenance. Compatibility with these other systems is essential for efficient exchange of information. Additional considerations are data storage capacity. Is there enough storage for all PMS data, past, present and future? Easy access with data integrity. Everyone should be able to look at data but not change it. Are there important restrictions on who can enter and edit PMS data? Proper support. If the agency mainframe will handle the PMS, can the data processing department provide support? If not, get a microcomputer. Flexibility. If the PMS changes, can the DBMS, can it add or delete fields, can it provide space for later use? Convenience. Is it easy to learn and use? Does it have menu choices, interactive data processing, ad hoc reporting capabilities, clear error messages and warnings and context sensitive health? Efficiency. Is it powerful enough to be fast? Hardware and memory prices are dropping. There is no excuse for wasting personnel time while waiting on underpowered computers. Security. Is the database protected from inadvertent or intentional damage? Some users need read-only access while others may need to be able to edit data. And quality assurance. Will the system have periodic checks to be sure data meet predefined standards? Will it check for both data errors and suspect data? In this program we have covered pavement management system data collection methods, road inventory, pavement condition, traffic data, maintenance, rehabilitation and reconstruction history, and cost data. In order to conduct a road inventory, each road must first have a unique identifier. Another category of data is pavement condition. Pavement condition surveys aid in monitoring pavement deterioration. Common indicators are physical distress, ride quality or roughness, and safety. Another category is traffic data. Engineers use traffic volume and axle load data to evaluate pavement performance, determine priorities and select appropriate treatments. They use mix of traffic as well, including annual average daily traffic and the percentage of cars, trucks of various weight classes, and buses. Road history data is another important category. Most PMS models require information on maintenance, rehabilitation and reconstruction projects. The database should have the date and type of construction, plus thickness and type of material. Historical costs of maintenance are the last data category. Engineers use them in the PMS life cycle cost analysis. These costs are not as predictable as construction costs because of the many factors that affect them. For more information on this or other IRF videotapes, write to the International Road Federation or call the numbers on your screen.