This project empirically characterizes primary and secondary truck markets and develops a simulation framework to examine how turnover dynamics shape technology diffusion.
This project developed a machine vision vehicle identification model to accurately and reliably quantify on-road fleet compositions characterized by a mix of vehicle types.
This project will package research findings on machine vision algorithms for vehicle identification into a deployable, open-source Automated Fleet Classification Toolkit for practitioners and researchers.
