In this blog, we use data visualization and data analytics to provide some basic understandings of the origin-destination (O-D) flows between stations in a bike-sharing system. Part of this blog is adapted from the following research paper: X. Xie and Z.
We perform a systematic analysis on the large-scale taxi trip data to uncover urban mobility and city dynamics in multimodal urban transportation environments. As a case study, we use the taxi origin-destination trip data and some additional data sources in
The system is a real-time, adaptive traffic control system (or the Internet of Smart Intersections, in the sense of Smart IoT) that optimally schedules dynamic traffic flows in complex urban road networks, by integrating traffic theory with artificial intelligence (AI). X.-F. Xie, et al.
During January 11-14, we presented our work on understanding and improving urban mobility at the Transportation Research Board (TRB) 94th Annual Meeting in the Walter E. Washington Convention Center, Washington, DC. An empirical study of combining participatory and physical sensing to
For solving problems in multimodal traffic and transportation networks and achieving sustainable urban mobility, we have worked on creating Smart and Scalable Urban Signal Networks and multimodal extensions, designing Intelligent Route Choice Framework, and utilizing Big Data and Urban Informatics. Publications X.-F. Xie, Z.-J.
On Aug 11-12, we attended Workshop on Big Data and Urban Informatics, with support from the National Science Foundation, held at the University of Illinois at Chicago (UIC).“The workshop brought together researchers from diverse disciplines motivated by sustainability and social