Introduction
The Research Group of Intelligent Transportation aims to solve intercity and intracity transportation problems by developing cutting-edge theories and methodologies. The Internet of Thing technologies enable different devices to communicate on an interconnected network. Such heterogeneous data sources are used to support the next generation intelligent transportation systems. To address the low quality of spatio-temporal transportation data, our research group focus on data fusion and data sensing techniques, spatio-temporal processing and indexing to increase the data usability. To support next generation intelligent transportation systems, our research group also study the latest techniques on data privacy, cloud computing, and Blockchain technologies.
Representative Research
Spatio-temporal crowdsourcing, data management, and query processing
To support intelligent transportation for smart city, we plan to study a systematic and comprehensive framework to tackle cutting-edge research problems in many aspects, including transportation data collection and data fusion by spatial crowdsourcing techniques, new deep-learning models for transportation problems, a ...
Large scale transportation data fusion and data processing
Intelligent transportation system data is multi-source with high variety. It covers several ways of residential mobility, including rail transit, route transit, floating cars and human walking trips. Different vehicles or human walking provides different data sources for ITS data and generally, the data formats from d ...