Transportation Typology

Transportation typology research aims to classify cities based on their transportation characteristics, enabling better urban planning and policy-making. Current efforts focus on developing machine learning models, often leveraging natural language processing techniques like sentence-BERT to analyze readily available textual data such as Wikipedia articles, and also employ novel autoencoder architectures for analyzing visual data like video and skeleton action data. This work is significant because it addresses the scarcity of labeled data in this field, allowing for scalable analysis of transportation systems across numerous cities worldwide and potentially improving the accuracy and efficiency of data analysis for large datasets.