Abstract:
The demands for the improvement of provincial roads are ever increasing and GOSL has given priority for the uplif ment of rural economy through the improvement of rural road network. Funding agencies have shown interest in providing financial assistance for this task. Road design engineers require reliable traffic data and design specifications for detailed design of provincial roads. One of the basic inputs required for the pavement design is the ESAL values for each vehicle category in each road. The most common method used for the estimation of ESAL values for trucks is the static axle load survey conducted by RDA for national roads. The axle load surveys are rarely done for provincial roads. Different approaches have been adopted for the estimation of truck factors for provincial roads. Lack of institutional arrangements, inadequacy of funds, lack of technical knowledge and equipment are the main reasons for the inability to carry out proper studies in this sector. Currently used axle load survey methods and their errors are being discussed under literature review. A simple but accurate methodology is required for the estimation of axle loads. The main objective is to find out > How to estimate the truck loads from visual observation > Then how this load is distributed among the axles A good vehicle classification system is highly desirable for provincial road network in order to find out ESAL values. The vehicle load can be estimated using first principles. The historical axle load survey data shall be used to derive a relationship for the distribution of vehicle load between axles. Then the results will be used for the estimation of ESAL for a sample road. The analysis of results will be done with probability approach. The results will also be checked and verified for accuracy and reliability. Actual axle load survey data will be used for this verification. A simple yet very effective method for the estimation of truck factors shall be introduced for the provincial roads. Most of the provincial road agencies can use this method to find out ESAL values for the entire road network with the available resources. Further recommendations will be made for further improvements on the methodology to improve the reliability of result. iii
