The 4th International Conference on Road and Airfield Pavement Technology (ICPT 2002) Development of a Comprehensive Pavement Management Information Systems

摘要

This paper describes the development of a comprehensive pavement management information (PMIS) system for the city of Toledo, Ohio, U.S.A. The city has a paved street network of approximately 1, 100 miles, of which about 360 miles are considered major roads with a traffic volume of greater than 600 per day. The rest are considered as secondary and residential streets. Instead of using off-the-shelf commercial software or hiring out the work to an outside contractor, the City and the University of Toledo developed a partnership to design and implement a PMIS that uses the state-of-the-art technologies and responses to the specific needs of the city. The PMIS uses a geographic information system (GIS) -Arc View by ESRI -- as its presentation module and includes a number of other modules. Data base module stores pavement inventory and condition data in a custom-designed Microsoft Access database, which facilitates data input and update. The major streets are dynamically segmented while the residential streets are management by pavement sections between two intersections. Current condition data are collected using a van equipped with laser profiler (for measuring ride quality) and digital camera (for surveying surface distresses). Most of the data processing tasks have been automated, so the chance for operator induced error has been minimized. At the heart of the PMIS is a module that predicts pavement performance based on past and current conditions, expected traffic loading, pavement structure, materials, and climatic environment. This pavement performance prediction module is crucial in supporting the PMIS to provide a multiyear work plan. Since the City had had little record regarding its pavement performance prior to this project, a condition prediction model were assumed initially and updated as actual data are accumulated. A multiyear optimization module then uses current and predicted conditions, specific distresses and likely treatments, traffic volume, available budget, and other constraints to determine a five-year work plan for the entire network. Since the city is geographically (and politically) divided into six city council districts, the optimization module takes into account the need to balance the repair work among the six districts.