Funded by a US$3.2 million grant from the US Department of Energy, the project will introduce multimodal transport hubs in selected neighborhoods. These ‘mobility zones’ in the Tennessee city will integrate buses, on-demand shuttles, electric vehicles and bike shares, coordinated through AI to recommend optimal routes and modes of transport to users in real time.
Cornell researchers are contributing to both the demand and supply sides of the project. On the demand side, Professor Ricardo Daziano, from Cornell’s Civil and Environmental Engineering Department, is leading the development of a choice-based recommender system that applies economic modeling to align transport options with individual preferences and constraints.
“Our system will exploit economic modelling to align individual preferences with real-time supply, allowing agencies to optimise service based on actual behavioural patterns–not just forecasts”
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