Research Scholar
Chun Liu, Department of Civil and Environmental Engineering and Geodetic Sciences
Ron Li, Faculty advisor
Biography
Dr. Chun Liu works as an associate professor at the Department of Surveying and Geo-Informatics, Tongji University, Shanghai, P. R. China. He got his PhD in Geographical Information System (GIS) from Tongji University in 2000, and is currently working in spatial data quality control and system integration of 3S technologies. His research interests focus on spatial data modelling, spatial data quality, image data processing, and integrated geographical data and GPS measurements for engineering applications. As a Visiting Scholar at The Ohio State University from Sep 2007 to Sep 2008, he is working for the basic research on Photogrammetry and Remote Sensing.
About the Research
The acquisition of accurate and timely traffic information is a vital precondition to rational traffic decision making. Intelligent Transportation Systems (ITSs) are bound to be the outcome when the modern traffic system develops to a high degree. In ITSs, instantaneous traffic information can be collected by the Floating Car Data (FCD) method. Based on the establishment of “Shenzhen Urban Transportation Simulation System” (SUTSS) in China, the researchers explored how to use 4000 taxis as the data collection sensors in Shenzhen, a southern city in China which borders Hong Kong. The researchers introduced the procedures and algorithms for the computation and map-matching of road segment velocities to a digital road network. To superimpose the near real-time traffic information onto a digital map, coordinate transformation is required and the transformation precision is analyzed using field testing data. Due to the nature of FCD, continuous GPS data such as routing velocities and coordinates can be collected by any GPS-equipped vehicle. Therefore, relevant algorithms are developed and utilized for the map-matching according to probability and statistical theories. To evaluate the reliability of proposed map-matching method, the confidence levels are calculated statistically, from which it can be determined whether the positioning data is valid or not with predefined threshold values. Furthermore, road segment velocity matching methods based on the Metropolis criteria is extended and relevant validation is carried out through the comparison of estimated and measured results. The major objective of this method is to obtain more accurate road segment travel time through the combination of those estimated by FCD and historical ones. This can significantly improve the reliability of instantaneous traffic information before its web publication. The final part of the research project introduced the architecture and the realization of a web Geographical Information System (GIS) and FCD-based instantaneous traffic information dissemination system for the whole of Shenzhen City.