Transportation Mobility Factor Extraction Using Image Recognition Techniques

For an urban development, the Quality of Life (QOL) of people in the city is a vital issue that should be considered. There are many researches in QOL topics that use questionnaire survey approach. These studies yield very useful information for city development planning. As the Artificial Intelligence technologies are developed very fast recently, they are applied to solve many transportation problems. In this paper, we propose a method that automatically extract mobility indicators using two image recognition techniques: Semantic Segmentation and Object Recognition. Because the mobility is an important factor in QOL evaluation, our work can be used to enhance a performance and reduce a data gathering cost of the QOL evaluation.