Abstract
This chapter presents methods in monitoring mobility systems afforded by the emergence of Big Data, smart cities, and Internet of Things. Definitions and examples are provided for the emerging trends. Mobility monitoring is one application that benefits from these advances. Three monitoring techniques are presented: one based on monitoring the “pulse” of a location, one on the “pace” of individual vehicle trajectories over time, and a third on the “travel momentum” of a population. The travel momentum is linked to time geography and is characterized by vector fields in space-time. Examples demonstrate its use to track scalar flow as well as direction, which in turn can be used to measure “impulses” or change in momentum as a before-after study. It can also be used to quantify its spatial-temporal relation with transport systems or points of interest through vector projections. The advantage of the travel momentum fields is that initial trajectory information can be preprocessed so that online updates are made possible with computationally cheap updates.
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