Harnessing the Geospatial Data Revolution to Empower Smart Transport and Enhance Road Safety

2024-10-04

Dr. Xiao Li

With the advancement of new and scalable data sources, robust acquisition methodologies, and transmission techniques, unprecedented amounts of traffic information are being generated and collected from various data sources, such as wearable biosensors, remote video, street-view imagery, GPS-enabled smartphones, (geo)social media, and connected & autonomous vehicles (CAVs). Compared to conventional traffic data, these emerging geospatial data sources provide researchers with rich and timely information to depict the road environment details, monitor traffic flow dynamics, capture/predict traffic conflicts, detect driving behavioral changes, and assess travel risk perceptions, among others. In this presentation, Dr Xiao Li will showcase some research projects, highlighting the applications of emerging geospatial data in road asset management and road safety assessment. Additionally, possibilities for future engagement and research will also be discussed. Bio: Dr Xiao Li is a Senior Researcher at the Transport Studies Unit of the University of Oxford. He is also a ‘Bryan Warren’ Junior Research Fellow at Linacre College Oxford. His research lies at the intersection of Geographic Information Science (GIS), Spatial Data Science, and Transport Geography. Dr Li received his PhD in Geography (GIS Transport) from Texas A&M University in 2019. Before joining TSU, he worked as an Associate Transport Researcher at Texas A&M Transportation Institute. Dr Li has led and participated in multiple projects sponsored by USDOT, FHWA, TxDOT, and US National University Transportation Centres (UTC). Currently, Dr Li serves on the Transportation Research Board (TRB) Standing Committee on Geographic Information Science in the US. He is also a management committee member of the Transport Statistics User Group and RGS-IBG GIScience Research Group in the UK.