Development of road maintenance fund allocation formula for Rwanda

Abstract

Feeder roads have a good impact on rural and centers development and are the cornerstone to facilitate economic activities, improve access to essential services such as health services, markets and commercial exchanges, agricultural products trading and provision of needs for farmers, and development of rural centers. The economic challenges to develop and maintain feeder road networks are still posing a need to develop a desk study tool to forecast the needed cost for maintenance over a visional set of years plan to maintain feeder roads. This study objective focused on the evaluation of maintenance standards for bitumen treated and gravel feeder roads, provision of maintenance intervention criteria that optimize feeder road condition for all-weather functioning, and development of feeder road maintenance cost prediction formula. The methodology that was used in this study applied the analysis of primary data using the HDM-4 analysis tool. Based on the latter analysis outputs (roughness condition and maintenance cost), maintenance standards, and intervention criteria that optimize all-weather road functioning conditions were defined for the local condition. Also, using the Multiple Linear Regression Analysis (MLRA) toolbox in Excel, maintenance prediction formulae were developed. The results of ANOVA showed that road width, length, traffic amount (AADT), and monthly average precipitation are statistically significant independent variables for and affect road maintenance costs, and the developed models' worthiness were found high with R-square values greater than 0.90 and other ANOVA statistical parameters such T-statistic, F-statistic and Pvalue significance showed that all independent variables are significant. The road maintenance cost prediction models/ formulae, maintenance standards, and intervention criteria in this study are vital to helping for sustainable maintenance planning and practices.