In the Era of Digitalization, all transportation data could be recorded in a high resolution in both space and time dimensions. The High Definition (HD) map could be accurate to the centimeter, providing data such as precise location of lane boundaries, width, and how they interconnect. Vehicles’ statuses such as position, speed, acceleration could be recorded every second or even lower. It could be an opportunity and also a challenge for transportation researchers to investigate how to fully use such high-resolution data, without missing any useful information. In this presentation, Dr. Cai will introduce his research about making better transportation safety prediction, which will cover: (1) How to prepare for a high-resolution data; (2) How to generate new “Fake” data as complementary data source; (3) How to make better transportation safety prediction by using deep learning technologies.
Dr. Cai is now a research assistant professor with the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida. Dr. Cai obtained Ph.D. from the University of Central Florida in 2017. He also received his Bachelor and Master Degrees in from Tongji University in 2011 and 2014. He has published 8 SCI/SSCI papers as first/corresponding author, and 3 of them are ESI highly cite papers.