Towards a Trajectory-powered Foundation Model of Mobility

• This paper advocates for a geospatial foundation model based on human mobility trajectories in the built environment. Such a model would be widely applicable across many important societal domains currently addressed independently, including transportation networks, data-driven urban planning, tourism, and sustainability. Unlike existing large vision-language models, trained primarily on text and images, this foundation model should integrate the complex spatiotemporal and multimodal data inherent to mobility. This paper motivates this challenging research agenda, outlining many downstream applications that would be significantly impacted and enabled by such a model. It then explains the critical spatial, temporal, and contextual factors that such a model must capture in trajectories. Finally, it concludes with several research questions and directions, laying the foundations for future exploration in this exciting and emerging field.

Geospatial Reasoning: Unlocking insights with generative AI and multiple foundation models

• Last November we introduced two pre-trained, multi-purpose models to address many of the challenges of geospatial modeling: the Population Dynamics Foundation Model (PDFM), which captures the complex interplay between population behaviors and their local environment, and a new trajectory-based mobility foundation model. Since then, over two hundred organizations have tested the PDFM embeddings for the United States and we are expanding the dataset to cover the UK, Australia, Japan, Canada, and Malawi for experimental use by selected partners.

• Social trajectories would be a straightforward adaptation of these models

Tasks

• Delete old objects – done
• Reach out to Chen Qifan?
• Plant plants – beds are done. Broke a soaker hose that I have to replace. Still need to do the flower boxes
• 4:00 Fidelity – done. Interesting!

SBIRs

• 10:00 SAIC meeting – need to put together a slide. Nope, couldn’t agree on what to do.