In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.
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Xianrui Xu obtained his B.S. in College of Environment and Planning, Liaocheng University, China in 2007, and M.S. in College of Resources and Environmental Science, East China Normal University, China in 2010. Now, he is a candidate of Ph.D. in School of Transportation Engineering, Tongji University, China and majors in transportation information engineering and control. His research interests refer to GIS-T, GPS trajectory analysis and modeling, and spatial data mining. During 2007 to 2012, he has participated several research projects, which include Natural Science Foundation of China (NSFC), National High Technology Research and Development Program (863 Program), etc. Moreover, he has published six papers in the core journals.
Xiaojie Li obtained his B.S. in School of Environment & Planning, Henan University, China in 2008 and M.S. in College of Resources and Environmental Science, East China Normal University, China in 2011. Now he works with ZTE Corporation, a world-class communication company. His research interests refer to GIS-T, GPS trajectory analysis and modeling, and spatial data mining.
Yujie HU obtained his M.S. degree with a major of GIS, in Key Laboratory of Geographical Information Science (Ministry of Education) in East China Normal University in Shanghai, China in 2012. Currently, he is a Ph.D. student majoring in GIS in Louisiana State University in Baton Rouge, USA. His research interests include GIS for transportation, spatial operational research, spatial modeling and information retrieve, etc. Some preliminary results have been published in journals or conference proceedings. Up to now, he has taken part in several research projects. In 2011, he won the funding provided by East China Normal University to visit the Department of Geography in the University of Utah in Salt Lake City, USA for half a year.
Zhongren Peng is a lifetime professor in department of urban and regional planning, University of Florida, US and also a Distinguished Professor of Cheung Kong Scholars Program in Tongji University, China. He is a transportation and planning scientist with above twenty years professional experience. He obtained his B.S. in department of geography, Central China Normal University in 1983 and earned his M.S. and Ph.D. degrees from Portland State University, Portland, US in 1994. His areas of expertise include geospatial information systems and analysis, information technology for planning, landscape planning using GIS and transportation. He has published more than 50 papers in international journal or conference and one English book named “Internet of GIS”. In addition, he has ever involved in and finished more than 10 projects, most of which were sponsored by Natural Science Foundation of China (NSFC), National High Technology Research and Development Program of China (863 Program), Ministry of Communications, US, etc.
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Xu, X., Li, X., Hu, Y. et al. A novel algorithm to identifying vehicle travel path in elevated road area based on GPS trajectory data. Front. Earth Sci. 6, 354–363 (2012). https://doi.org/10.1007/s11707-012-0340-0
- GPS trajectory
- vehicle status identification
- trajectory segmentation
- road network modeling
- elevated road