The project integrates multi-dimensional human perception data, collected using physiological sensors, with refined street-level built environment data, extracted using the latest computer vision techniques, to systematically understand how e-scooter riders and active travelers perceive the built environment and identify factors that influence travel satisfaction.
New modes of transportation have the potential to provide better access for all, including people with limitations due to age, physical fitness levels, or disabilities. The secret ingredient is to provide a safe street space that is welcoming to all users.
When deciding whether to use a shared dockless e-bike, docked bikeshare, or shared e-scooter, weather is often a factor in user decision making.
These NSF investments create scientific and engineering foundations for smart cities and communities and help enhance overall quality of life.