Transportation Engineering Road Safety Bayesian Statistics in Transport Remote Sensing Infrastructure Digitization
Dr. Karim El-Basyouny is an Associate Professor and inaugural City of Edmonton’s Research Chair in Urban Traffic Safety at the University of Alberta (UofA). In this role, he works alongside members of both the City of Edmonton and other transportation agencies to ensure sound scientific practices are maintained in the considerations of Alberta and Canada’s roadway infrastructure. He joined the UofA in July 2011 after completing his M.A.Sc. and Ph.D. in Transportation Engineering from the University of British Columbia. He is a co-founder and steering committee member for the Centre of Smart Transportation in the Department of Civil and Environmental Engineering. He is an active member of several national and international safety committees and serves on the editorial board of a number of prominent journals. He chaired the 2012 International Urban Traffic Safety Conference and 2016 Transportation Innovation Conference. Dr. El-Basyouny has won several research awards throughout his career, with his most recent being the UofA’s Faculty of Engineering Mid-career Research Award and the 2020 Canadian ITS R&D/Innovation Award.
Dr. El-Basyouny’s research focuses on developing models, techniques, and algorithms that can contribute to and improve the safety of human drivers and self-driving vehicles. Dr. El-Basyouny’s research on collision modeling and evaluation focused on applying Bayesian statistics to improve the predictive power and fit of existing safety models as well as to address several key data and methodological issues. His work on speed management focused on understanding the risk and factors that influence speeding in urban environments and developing programs to increase compliance to speed limits and improve safety. This included a comprehensive body of work on the impacts of speed limit reductions, the use of automated enforcement, and ITS technologies. Dr. El-Basyouny’s recent research has been directed at developing a framework combining advanced sensor technologies with data-processing tools to automatically detect and extract road and roadside features. Through an interdisciplinary approach, Dr. El-Basyouny combines statistical pattern recognition techniques and machine learning tools for the semantic segmentation of 3D point cloud data. His work in this area investigates the safety and mobility benefits of digitizing roadway infrastructure.
Introduction to traffic safety. Focus on collisions and exposure. Safety management process. Collision modeling, theory and applications. Safety evaluation techniques, challenges, opportunities, influence of confounding factors and regression to the mean bias.Fall Term 2020
Prerequisites: permission of Department or Instructor. In this course various advanced topics on transportation engineering and planning will be taught. Some possible advanced topics are: advanced probability theory, traffic safety, travel survey method, ITS technology, advanced network analysis, travel behaviour analysis, integrated land use and transportation modelling, public transportation planning and designing, freight transportation, transportation logistics and operation research. New topics may be added later by the Instructors.Winter Term 2021