Open Street

OpenStreetMap (OSM) data is increasingly leveraged in diverse applications, ranging from urban planning and traffic management to autonomous vehicle navigation and land cover mapping. Current research focuses on using OSM in conjunction with advanced machine learning techniques, such as deep reinforcement learning and graph neural networks, to optimize urban infrastructure initiatives like open streets programs and improve the accuracy of high-resolution land cover maps. These advancements contribute to more efficient resource allocation, improved safety assessments, and enhanced capabilities for autonomous systems operating in various environments.