Road pavement is a supporting factor for national development, especially in the distribution of trade in goods and services as well as the movement of human mobility. Road maintenance needs to be done regularly so that the road is always in good condition, but the weather and road loads are the things that cause road damage. Road damage is generally categorized into cracks, alligator cracks and potholes. The purpose of this research is to utilize image processing to detect and classify the types of road damage. The steps involved include: image acquisition with a digital camera, conversion of RGB images into grayscale images, image normalization, selection of damage points, counting histogram bins, determining damage bins, calculating noise with image morphology (closing and opening) using a disk element structure of size 5, calculating radial vector and finally classifying road damage using the K-NN (K Nearest Neighbor) method with 3 classes and a K value of 11. The image from the classification results is then calculated the level of damage based on the category according to the SDI (Surface Distress Index) provisions, where the level of crack damage is seen from the width of the crack, the alligator crack is seen from the percentage of damaged area compared to the segment under review and the pathole is seen from many holes. The test used 597 images consisting of 95% training data and 5% test data, the results obtained that the accuracy of this research reached 83%.
Abstract. Sustainable transport is closely related to quality of life in the community at present and in the future. Some indicators of transport sustainability are accessibility measurement of origin/destination, the operating costs of transport (vehicle operating cost or VOC) and external transportation costs (emission cost). The indicators could be combined into accessibility measurement model. In other case, almost traffic congestion occurred on the condition of mixed traffic. This paper aimed to analyse the indicator of transport sustainability through simulation under condition of various traffic composition. Various composition of truck to total traffic flow are 0%, 10% and 20%. Speed and V/C are calculated from traffic flow to estimate the VOC and emission cost. 5 VOC components and 3 types of emission cost (CO2, CH4 and N2O) are counted to be a travel cost. Accessibility measurement was calculated using travel cost and gravity model approaches. Result of the research shows that the total traffic flow has indirect impact on accessibility measurement if using travel cost approach. Meanwhile, the composition of traffic flow has an affect on accessibility measurement if using gravity model approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.