Prof Shan Lin from ECE will present:

In this talk, Lin will discuss research on real-time collaborative
sensing, modeling, data analysis, and model predictive control for urban
transportation systems, especially taxi networks. The goal is to
significantly enhance the efficiency of existing transportation
systems. Traditional transportation systems are usually based on limited, isolated, and rough grained knowledge about human mobility patterns. For example, taxi
networks heavily rely on drivers' experience to look for passengers on the
street; bus and subway networks employ fixed schedules and routes. As
sensing devices (GPS, occupancy sensors, cameras, and smart transit cards
etc) are deployed pervasively into these transportation systems, large
amount of real-time human mobility information become available. Such data
sets not only reveal the spatiotemporal dynamics of the human mobility, but
also indicate the correlations among various urban phenomena.