A project implemented by the city of Edmonton, Alberta, Canada, that repurposed several travel lanes served as a case study. Using video data, researchers Maged Gouda, S.M.ASCE; Jie Fan; Kelly Luc; Shewkar Ibrahim, Ph.D., P.Eng.; and Karim El-Basyouny, Ph.D., P.Eng., investigated the effectiveness of the redesign, usage patterns, physical distancing violations, and the impact the redesign had on traffic safety. The video footage covered all the shared spaces, and the team was able to account for accurate measurement of distances to check compliance.
Their paper published in the Journal of Transportation Engineering, Part A: Systems, entitled “Effect of Redesigning Public Shared Space Amid the COVID-19 Pandemic on Physical Distancing and Traffic Safety” will help transportation agencies in redesigning public spaces for the current pandemic and provide insight on the effectiveness of redesigns for any future pandemics.
Read about their use of computer vision–based techniques to detect road users in video data in the abstract below or by reading the full paper in the ASCE Library: https://doi.org/10.1061/JTEPBS.0000596
Abstract
The concept of redesigning public spaces to encourage physical distancing amid the COVID-19 pandemic is being tested around the world. In Canada, municipalities are reallocating underutilized road lanes for active modes of transportation, such as walking and cycling. We evaluated the usage and benefit of these shared spaces to ensure redesign efforts are optimally allocated. We analyzed two sets of closed-circuit television (CCTV) footage before and after the change, covering April 7–13, 2020, at two locations using automated computer vision techniques. We detected and recorded physical distancing violations, traffic safety risks such as midblock crossing, speeds, and traffic conflicts, and generated trajectory maps of all road users. It was found that the redesign was utilized effectively by road users and improved physical distancing compliance without compromising traffic safety. The proposed framework also provides an innovative tool to automatically gather, extract, share, and analyze real-world data to improve response to the COVID-19 pandemic as well as future outbreaks of contagious disease.
Read the full paper in the ASCE Library: https://doi.org/10.1061/JTEPBS.0000596
