Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
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TY - CONF
T1 - Multi-source data integration-based urban road GPS environment friendliness estimation
AU - Ma, L.
AU - Wang, Y.
AU - Peng, G.
AU - Zhang, C.
AU - Chen, C.
AU - Zhao, J.
AU - Wang, J.
N1 - Export Date: 29 April 2020 Correspondence Address: Wang, Y.; Key Laboratory of High Condence Software Technologies, Ministry of EducationChina; email: wangyasha@pku.edu.cn Funding details: National Natural Science Foundation of China, NSFC, 61772045 Funding text 1: This work is supported by the National Natural Science Foundation of China (No.61772045).
PY - 2019
Y1 - 2019
N2 - In urban areas, multipath errors may occur due to blockage and reflection of GPS signals by buildings, and significantly reduce the accuracy of GPS positioning. The degree to which the environment causes multipath errors and negatively impacts GPS accuracy is referred to as GPS Environment Friendliness (GEF) in this paper. The estimation of GEF helps location-based-service remind users to reduce the psychological expectation of GPS accuracy when they enter a poor GEF area. While existing studies estimate the GEF only based on the vehicle trajectory data, we propose a more efficient matrix completion-based approach that uses the historical bus trajectory data with the integration of the building layout information and road tag information. Based on one month GPS trajectory data of 4835 buses within the second ring road in Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests. © 2019 IEEE.
AB - In urban areas, multipath errors may occur due to blockage and reflection of GPS signals by buildings, and significantly reduce the accuracy of GPS positioning. The degree to which the environment causes multipath errors and negatively impacts GPS accuracy is referred to as GPS Environment Friendliness (GEF) in this paper. The estimation of GEF helps location-based-service remind users to reduce the psychological expectation of GPS accuracy when they enter a poor GEF area. While existing studies estimate the GEF only based on the vehicle trajectory data, we propose a more efficient matrix completion-based approach that uses the historical bus trajectory data with the integration of the building layout information and road tag information. Based on one month GPS trajectory data of 4835 buses within the second ring road in Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests. © 2019 IEEE.
KW - GPS positioning error
KW - Location based service
KW - Map matching
KW - Matrix completion
KW - Behavioral research
KW - Global positioning system
KW - Location based services
KW - Multipath propagation
KW - Road vehicles
KW - Roads and streets
KW - Smart city
KW - Telecommunication services
KW - Trajectories
KW - Trusted computing
KW - Ubiquitous computing
KW - Building layout
KW - Environment friendliness
KW - GPS positioning
KW - Gps trajectories
KW - Multi-source data integrations
KW - Multipath error
KW - Vehicle trajectories
KW - Data integration
U2 - 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00144
DO - 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00144
M3 - Conference paper
SP - 626
EP - 633
ER -