Analyzing and modeling network travel patterns during the Ukraine invasion using crowd-sourced pervasive traffic data
Journal: arXiv (Cornell University)
Year: 2022

In 2022, Ukraine is suffering an invasion which has resulted in acute impacts playing out over time and geography. This paper examines the impact of the ongoing disruption on traffic behavior using analytics as well as zonal-based network models. The methodology is a data-driven approach that utilizes obtained travel-time conditions within an evolutionary algorithm framework which infers origin-destination demand values in an automated process based on traffic assignment. Because of the automati