Vehicle Trajectory Reconstruction and Home Places Estimation from Monitoring Data
Analyzing vehicle travel information and roadway network traffic state of perception data has been a popular research topic. In order to excavate the vehicle travel characteristics in the city of Rui’an from monitoring data, the authors proposed a trajectory reconstruction model integrated into the ordered weighted averaging (OWA) and setting four attributes to solve trajectory records missing phenomenon, the authors verified the model’s reliability through actual experiments. Then they devised a method combining two algorithms to estimate the important places of each individual vehicle based on the reconstructed vehicles trajectory. The authors' results showed that the method using the K-means algorithm makes good predictions: 97% of the distances between the actual places and estimated places are within 2 km. Both the trajectory reconstruction and home places estimation will provide data support for studying vehicle commuting and road network characteristics.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
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Supplemental Notes:
- © 2018 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Yu, Haiyang
- Yang, Shuai
- Liu, Shuai
- Ren, Yilong
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Conference:
- 18th COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2018-7-5 to 2018-7-8
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 2203-2212
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Commuting; Data mining; Networks; Roads; Traffic flow; Traffic surveillance; Trajectory; Travel patterns
- Geographic Terms: Rui'an (China)
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01874430
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Feb 23 2023 1:15PM