Some road systems are unpaved due to limited governmental finance and fewer maintenance techniques. Such unpaved roads become vulnerable during heavy rainy seasons following restrained accessibility among cities and traffic accidents. Considering the circumstances, innovative and cost–effective approaches are required for unpaved roads. Microbially induced carbonate precipitation (MICP) is an emerging soil improvement technology using microbes to hydrolyze urea generating carbonate ions, and precipitates calcium carbonate in the presence of calcium ion. Induced calcium carbonate bonds soil particles enhancing stiffness and strength when the MICP reaction takes place within the soil system. This study introduces the use of microbes on unpaved road systems consisting of in situ lateritic soils. The MICP technology was implemented to improve soil strength through two approaches: surface spraying and mixing methods. A series of soil testing was performed with varying chemical concentrations to measure precipitation efficiency, strength, and quality for construction material and see the feasibility of the proposed methods. The laboratory test results indicated that the surface spraying method provided improved; however, it was highly affected by the infiltration characteristics of used soils. The mixing method showed promising results even under submerged conditions, but still required improvement. Overall, the proposed idea seems possible to apply to improving unpaved road systems in the lateritic region but requires further research and optimization.

The objective of this study is to provide a process that can be applied in preparation for the introduction of an efficient and systematic pavement management system. This process includes features for selecting pavement segmentation (for management) and priority based on a cumulative difference approach(CDA), starting from the development of an index that reflects the pavement condition and current distribution status. For the index, which can reflect the current pavement conditions of sections to be managed, this study proposes a basic model form and establishes a simple modeling plan that uses only 3 points (maximum value, minimum value, and management standard) for typical flaws. For pavement segmentation, this study establishes a plan that uses a moving average combined with a minimum maintenance length standard to reflect existing condition distribution characteristics as much as possible. Finally, for priority, this study establishes a plan that performs selections using the averages of the index values of the sections that require maintenance, as determined via the segmentation step.