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Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach †
GPS is taken as the most prevalent positioning system in practice. However, in urban areas, as the GPS satellite signal could be blocked by buildings, the GPS positioning is not accurate due to multi-path errors. Estimating the negative impact of urban environments on GPS accuracy, that is the GPS e...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146484/ https://www.ncbi.nlm.nih.gov/pubmed/32178298 http://dx.doi.org/10.3390/s20061580 |
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author | Ma, Liantao Zhang, Chaohe Wang, Yasha Peng, Guangju Chen, Chao Zhao, Junfeng Wang, Jiangtao |
author_facet | Ma, Liantao Zhang, Chaohe Wang, Yasha Peng, Guangju Chen, Chao Zhao, Junfeng Wang, Jiangtao |
author_sort | Ma, Liantao |
collection | PubMed |
description | GPS is taken as the most prevalent positioning system in practice. However, in urban areas, as the GPS satellite signal could be blocked by buildings, the GPS positioning is not accurate due to multi-path errors. Estimating the negative impact of urban environments on GPS accuracy, that is the GPS environment friendliness (GEF) in this paper, will help to predict the GPS errors in different road segments. It enhances user experiences of location-based services and helps to determine where to deploy auxiliary assistant positioning devices. In this paper, we propose a method of processing and analysing massive historical bus GPS trajectory data to estimate the urban road GEF integrated with the contextual information of roads. First, our approach takes full advantage of the particular feature that bus routes are fixed to improve the performance of map matching. In order to estimate the GEF of all roads fairly and reasonably, the method estimates the GPS positioning error of each bus on the roads that are not covered by its route, by taking POIinformation, tag information of roads, and building layout information into account. Finally, we utilize a weighted estimation strategy to calculate the GEF of each road based on the GPS positioning performance of all buses. Based on one month of 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. |
format | Online Article Text |
id | pubmed-7146484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-71464842020-04-20 Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † Ma, Liantao Zhang, Chaohe Wang, Yasha Peng, Guangju Chen, Chao Zhao, Junfeng Wang, Jiangtao Sensors (Basel) Article GPS is taken as the most prevalent positioning system in practice. However, in urban areas, as the GPS satellite signal could be blocked by buildings, the GPS positioning is not accurate due to multi-path errors. Estimating the negative impact of urban environments on GPS accuracy, that is the GPS environment friendliness (GEF) in this paper, will help to predict the GPS errors in different road segments. It enhances user experiences of location-based services and helps to determine where to deploy auxiliary assistant positioning devices. In this paper, we propose a method of processing and analysing massive historical bus GPS trajectory data to estimate the urban road GEF integrated with the contextual information of roads. First, our approach takes full advantage of the particular feature that bus routes are fixed to improve the performance of map matching. In order to estimate the GEF of all roads fairly and reasonably, the method estimates the GPS positioning error of each bus on the roads that are not covered by its route, by taking POIinformation, tag information of roads, and building layout information into account. Finally, we utilize a weighted estimation strategy to calculate the GEF of each road based on the GPS positioning performance of all buses. Based on one month of 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. MDPI 2020-03-12 /pmc/articles/PMC7146484/ /pubmed/32178298 http://dx.doi.org/10.3390/s20061580 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ma, Liantao Zhang, Chaohe Wang, Yasha Peng, Guangju Chen, Chao Zhao, Junfeng Wang, Jiangtao Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title | Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title_full | Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title_fullStr | Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title_full_unstemmed | Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title_short | Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach † |
title_sort | estimating urban road gps environment friendliness with bus trajectories: a city-scale approach † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146484/ https://www.ncbi.nlm.nih.gov/pubmed/32178298 http://dx.doi.org/10.3390/s20061580 |
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