期刊
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
卷 30, 期 -, 页码 41-54出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2013.02.002
关键词
Map-matching; Path inference; Sparse floating car data; GPS
The use of probe vehicles in traffic management is growing rapidly. The reason is that the required data collection infrastructure is increasingly in place in urban areas with a significant number of mobile sensors constantly moving and covering expansive areas of the road network. In many cases, the data is sparse in time and location and includes only geo-location and timestamp. Extracting paths taken by the vehicles from such sparse data is an important step towards travel time estimation and is referred to as the map-matching and path inference problem. This paper introduces a path inference method for low-frequency floating car data, assesses its performance, and compares it to recent methods using a set of ground truth data. (C) 2013 Elsevier Ltd. All rights reserved.
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