Improving Efficiency of Metropolitan-Scale Transportation Systems With Multi-Modal Online Feeds
Traditionally urban transit services are historically designed based on limited sampling data through surveys and census, which are often dated and incomplete. Also, traditional theory and practice typically focus on isolated individual modes of transit. These two limitations result in unsatisfactory passenger experiences such as unnecessary detours and prolonged travel delays. Recent years have brought a growing opportunity: the massively online data feeds available now enable researchers to optimize urban transit systems from a multimodal online perspective with an unprecedented scale. This is because the availability of micro-level information about trips instead of macro-level statistics will make further performance optimization possible, and the freshness of the online feeds allows experts to build online systems to deal with rapid changes in the dynamic urban environment.
A bibliography of this group’s publications is attached.
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