  Shuttle buses have been a popular means to move commuters sharing similar
origins and destinations during periods of high travel demand. However,
planning and deploying reasonable, customized service bus systems becomes
challenging when the commute demand is rather dynamic. It is difficult, if not
impossible to form a reliable, unbiased estimation of user needs in such a case
using traditional modeling methods. We propose a visual analytics approach to
facilitating assessment of actual, varying travel demands and planning of night
customized shuttle systems. A preliminary case study verifies the efficacy of
our approach.
