Development of pavement management concepts for visual condition evaluations

Since the collection of detailed pavement condition data is costly and time consuming, innovative approaches for rapid data collection are in increasing demand especially among highway agencies with limited pavement management budgets. In the first phase of this research, a time saving and efficient data collection approach based on rapid visual observations is introduced for rating predominant asphaltic pavement distresses. Separate rating of both severity and extent of distress provides more information for eventual maintenance cost computations. Fuzzy sets techniques are used to deal with the subjectivity in human judgment of distress severity and extent. In addition, the relative impact of each distress type on maintenance is also utilized in the determination of the resultant condition index. A Fuzzy aggregation technique with a high computational efficiency for large databases is employed for prioritizing pavement sections with respect to rehabilitation needs. A future pavement condition forecasting model is also developed utilizing experienced highway maintenance engineers' assessment of pavement degradation rates associated with each distress type.; In the second phase of this research, an optimal pavement rehabilitation and maintenance decision-making methodology is formulated as a sequel to the pavement evaluation and prioritization techniques developed in the first place. In this exercise, first, a simple technique is spawned to forecast future maintenance costs associated with alternative rehabilitation strategies. In contrast to most existing models, the new decision-making model incorporates specific identification and the traffic (Equivalent Single Axle Loads) of each pavement section. The new formulation also accounts for both the agency cost and the user cost in the life-cycle cost analysis that eventually produces the optimum rehabilitation strategy for each pavement section based on dynamic programming. Consideration of both agency and user costs would naturally assure not only economic rehabilitation decisions but also satisfactory maintenance of the entire highway network. Secondly, even in the life-cycle cost analysis, appropriate fuzzy sets mathematical techniques are incorporated in manipulating visual condition data and subjectively expressed experienced maintenance related opinions.; In an accessory phase of this research, the GIS technology was introduced to enhance the process of pavement condition data collection and recording on a provincial basis. Since pavement management activities and related decisions are facilitated by effective visualization of spatial information, the developments in the first phases along with the use of GIS technology certainly offers enormous potential for meaningful budgeting and effective rehabilitation decisions in PMSs with limited budget. Finally, the applicability and significance of the above developments are demonstrated by performing a case study involving actual data and information collected from the major highways and Road Development Authority of Sri Lanka. Hence this research endeavor is expected to mete out a significant contribution to the formulation of a Pavement Management System for Sri Lanka, a vital project mandated by the World Bank and the International Monetary Fund.