Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm

Electronic maps play an important role in the field of urban traffic management, but the interface functions provided by map service agencies are limited, and commercial maps are generally expensive. Furthermore, the map generation algorithms based on the Global Positioning System (GPS) data can be...

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Main Authors: Jian Zhang, Shuai Ling, Ping Wang, Xiaoyang Hu, Lu Liu
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/10/12/1322
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author Jian Zhang
Shuai Ling
Ping Wang
Xiaoyang Hu
Lu Liu
author_facet Jian Zhang
Shuai Ling
Ping Wang
Xiaoyang Hu
Lu Liu
author_sort Jian Zhang
collection DOAJ
description Electronic maps play an important role in the field of urban traffic management, but the interface functions provided by map service agencies are limited, and commercial maps are generally expensive. Furthermore, the map generation algorithms based on the Global Positioning System (GPS) data can be very complex and take up a lot of storage space, which limits their application to specific practical problems, such as the real-time update of area maps, temporary road control, emergency route planning, and other scenarios. In order to solve this problem, an intuitive, extensible, and flexible method of constructing urban road maps is proposed. Using the Othello-coordinated method, the representation of the unit grid cell was redesigned. Through this method, the disadvantages of the raster map’s large storage space and computing resource requirements are compensated for during processing, improving the topological expression ability of the raster map and the speed with which the construction of the map is realized. The application potential of the proposed method is demonstrated by the evaluation of public transport service and road network resilience. In our experiments, the optimization efficiency of storage space was up to 99.914%, and the calculation accuracy of bus coverage was about 99.86%.
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spelling doaj.art-54c50fd02184417daf9f6d2960a3752e2023-11-23T09:10:46ZengMDPI AGLand2073-445X2021-12-011012132210.3390/land10121322Method for Fast Map Construction Based on GPS Data and Compressed Grid AlgorithmJian Zhang0Shuai Ling1Ping Wang2Xiaoyang Hu3Lu Liu4School of Electrical and Information Engineering, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, ChinaCollege of Management and Economics, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300192, ChinaCollege of Management and Economics, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300192, ChinaCollege of Management and Economics, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300192, ChinaSchool of Geographic and Environmental Sciences, Tianjin Normal University, No. 393, Binshui Road, Xiqing District, Tianjin 300382, ChinaElectronic maps play an important role in the field of urban traffic management, but the interface functions provided by map service agencies are limited, and commercial maps are generally expensive. Furthermore, the map generation algorithms based on the Global Positioning System (GPS) data can be very complex and take up a lot of storage space, which limits their application to specific practical problems, such as the real-time update of area maps, temporary road control, emergency route planning, and other scenarios. In order to solve this problem, an intuitive, extensible, and flexible method of constructing urban road maps is proposed. Using the Othello-coordinated method, the representation of the unit grid cell was redesigned. Through this method, the disadvantages of the raster map’s large storage space and computing resource requirements are compensated for during processing, improving the topological expression ability of the raster map and the speed with which the construction of the map is realized. The application potential of the proposed method is demonstrated by the evaluation of public transport service and road network resilience. In our experiments, the optimization efficiency of storage space was up to 99.914%, and the calculation accuracy of bus coverage was about 99.86%.https://www.mdpi.com/2073-445X/10/12/1322digital grid mapmap compressionmap splicingbus coverageresilient traffic
spellingShingle Jian Zhang
Shuai Ling
Ping Wang
Xiaoyang Hu
Lu Liu
Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
Land
digital grid map
map compression
map splicing
bus coverage
resilient traffic
title Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
title_full Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
title_fullStr Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
title_full_unstemmed Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
title_short Method for Fast Map Construction Based on GPS Data and Compressed Grid Algorithm
title_sort method for fast map construction based on gps data and compressed grid algorithm
topic digital grid map
map compression
map splicing
bus coverage
resilient traffic
url https://www.mdpi.com/2073-445X/10/12/1322
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