Urban Environment
Urban environment research focuses on understanding and improving various aspects of cities, from infrastructure and transportation to social dynamics and environmental impact. Current research employs diverse methods, including large language models (LLMs) for urban planning and autonomous systems, deep learning for image analysis and prediction of traffic flow and air quality, and advanced sensor fusion techniques like LiDAR and radar for navigation and mapping. These advancements are improving urban planning, resource management, and the development of safer, more efficient, and sustainable urban spaces, with implications for transportation, environmental monitoring, and public safety.
Papers
Towards a prioritised use of transportation infrastructures: the case of vehicle-specific dynamic access restrictions to city centres
Holger Billhardt, Alberto Fernández, Pasqual Martí, Javier Prieto Tejedor, Sascha Ossowski
The Locus Story of a Rocking Camel in a Medical Center in the City of Freistadt
Anna Käferböck, Zoltán Kovács
Geo-located Aspect Based Sentiment Analysis (ABSA) for Crowdsourced Evaluation of Urban Environments
Demircan Tas, Rohit Priyadarshi Sanatani
Point Cloud Segmentation Using Transfer Learning with RandLA-Net: A Case Study on Urban Areas
Alperen Enes Bayar, Ufuk Uyan, Elif Toprak, Cao Yuheng, Tang Juncheng, Ahmet Alp Kindiroglu