■ Title: Advancing Winter Transportation Safety and Mobility using Geostatistics and Deep Learning

■ Speaker: Professor Tae J. Kwon (Department of Civil & Environmental Engineering, University of Alberta)

■ Date: 3.9(Thu) 16:00

■ Venue: Munji Campus, L409

■ Abstract: Intelligent Transportation System (ITS) is an important part of modern transportation engineering and has a significant impact on improving traffic safety and mobility, particularly for cold regions that experience severe winter weather conditions. To help support and facilitate winter maintenance decisions, an advanced highway ITS monitoring technology; namely, Road Weather Information Systems (RWIS) has been deployed throughout many road networks around the world. However, despite their importance, the deployment is often limited due to its high installation and perpetual operating costs. Likewise, the existence of large spatial gaps between RWIS stations further hinders its full monitoring and estimation capabilities. In this seminar, I will introduce a hybrid methodological framework that combines geostatistics and deep learning to optimize RWIS networks and infer winter road surface conditions using North American case studies. The methodologies and findings presented in this seminar will help mitigate the negative impacts of winter weather upon the vast transportation systems in Canada and abroad as they seek to benefit all road users with improved safety, mobility and a more environmentally sustainable transportation system.