In urban transportation networks, the inefficiency of the road network is primarily caused by traffic bottlenecks. Freight bottleneck is a unique type of traffic bottleneck that exclusively involves the analysis of truck freight mobility. This research uses Geotab telematics data to detect and analyze long-term freight transportation bottlenecks at large-scale. This presentation includes an overview of the definition and detection of freight transportation bottleneck based on a database-parallel implementation of connected components algorithm and the ranking metrics for the utility function.
Yunfei Ma is a research consultant at Geotab Inc., working on developing computationally efficient algorithms and data pipelines for large-scale freight analysis and data-related products. His research focuses on emerging areas (theories and applications) in computational transportation science, including telematics data visualization, freight bottlenecks, freight transportation emission, and sustainable truck routing. For academic background, Yunfei graduated from the University of Illinois at Urbana-Champaign with a bachelor’s degree in Mathematics and Statistics and is now a second-year Ph.D. student in Computational Science and Engineering at McMaster University.