Modeling and predicting travel demand is vital for efficient planning and design of transportation solutions. Analyzing and modeling multi-modal travel patterns of people requires seamless capturing of all trips, including trip purposes and information about transport means people chose (car, bicycle, train, etc.), travel routes, transfer points and transfer times. Such information should be ideally collected for a minimum of one week for representative capturing of multimodal travel behavior.
Traditional mobility surveys require respondents to fill out trip diary forms and thus usually allow only relatively small samples and short survey periods. Providing survey respondents with dedicated devices such as GPS loggers induce additional cost and usually only provide location data. AIT develops solutions exploiting the fact that mobile communication between people with smartphones is ubiquitous today.
- Cellular Data Analytics: Powerful and thoroughly validated techniques for extracting key data from cellular phone networks for traffic demand modeling, including commuter flows, origin-destination matrices, travel times, activity patterns, etc.
- Smart Survey: Easy and accurate mobility surveys with respondents’ private Smartphones - a web-based service for cities, communities, traffic planners and mobility researchers; Distinguished features of the system are automatic detection of trip starts and trip ends and automatic inference of trip purposes, thus increasing accuracy and reducing impact on daily activities of respondents.