Big data is a very popular topic in recent years, and how to make full use of transportation big data is also drawing more and more attention of academia and society. However, transportation big data have their own inherent issues which cannot be ignored by researchers or users. In this lecture, we will share a deeper understanding of those issues from a different perspective in terms of two examples: Origin-Destination (OD) analysis and trip end identification. We hope to share the idea that it is necessary for us to keep mindful when using transportation big data since high quality data could lead to excellent results while misleading data may result in bad decisions.
Jingxing Wang is a PhD student of Department of Civil & Environment Engineering at University of Washington, Seattle. He joined in intelligent Urban Transportation Systems Lab (directed by Prof. Jeff Ban) of UW in the autumn of 2016 after obtaining his bachelor’s degree of Civil Engineering from Tsinghua University in 2016. His research interests include: transportation big data analytics, transportation network modeling, machine learning and optimization, and so on.