Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data
Purpose - There is a certain error in the satellite positioning of the vehicle. The error will cause the drift point of the positioning point, which makes the vehicle trajectory shift to the real road. This paper aims to solve this problem. Design/methodology/approach - The key technology to solve t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2019-03-01
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| Series: | International Journal of Crowd Science |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/IJCS-01-2019-0001/full/pdf?title=research-on-map-matching-algorithm-based-on-priority-rule-for-low-sampling-frequency-vehicle-navigation-data |
| _version_ | 1797991240415838208 |
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| author | Zhishuo Liu Yao Dongxin Zhao Kuan Wang Chun Fang |
| author_facet | Zhishuo Liu Yao Dongxin Zhao Kuan Wang Chun Fang |
| author_sort | Zhishuo Liu |
| collection | DOAJ |
| description | Purpose - There is a certain error in the satellite positioning of the vehicle. The error will cause the drift point of the positioning point, which makes the vehicle trajectory shift to the real road. This paper aims to solve this problem. Design/methodology/approach - The key technology to solve the problem is map matching (MM). The low sampling frequency of the vehicle is far from the distance between adjacent points, which weakens the correlation between the points, making MM more difficult. In this paper, an MM algorithm based on priority rules is designed for vehicle trajectory characteristics at low sampling frequencies. Findings - The experimental results show that the MM based on priority rule algorithm can effectively match the trajectory data of low sampling frequency with the actual road, and the matching accuracy is better than other similar algorithms, the processing speed reaches 73 per second. Research limitations/implications - In the algorithm verification of this paper, although the algorithm design and experimental verification are considered considering the diversity of GPS data sampling frequency, the experimental data used are still a single source. Originality/value - Based on the GPS trajectory data of the Ministry of Transport, the experimental results show that the accuracy of the priority-based weight-based algorithm is higher. The accuracy of this algorithm is over 98.1 per cent, which is better than other similar algorithms. |
| first_indexed | 2024-04-11T08:48:06Z |
| format | Article |
| id | doaj.art-edb532f5c790420bbc5692a19c442e62 |
| institution | Directory Open Access Journal |
| issn | 2398-7294 |
| language | English |
| last_indexed | 2024-04-11T08:48:06Z |
| publishDate | 2019-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | International Journal of Crowd Science |
| spelling | doaj.art-edb532f5c790420bbc5692a19c442e622022-12-22T04:33:53ZengTsinghua University PressInternational Journal of Crowd Science2398-72942019-03-013121310.1108/IJCS-01-2019-0001625977Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation dataZhishuo Liu0Yao Dongxin1Zhao Kuan2Wang Chun Fang3Beijing Jiaotong University, Beijing, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, ChinaHenan Polytechnic, Jiaozuo, ChinaPurpose - There is a certain error in the satellite positioning of the vehicle. The error will cause the drift point of the positioning point, which makes the vehicle trajectory shift to the real road. This paper aims to solve this problem. Design/methodology/approach - The key technology to solve the problem is map matching (MM). The low sampling frequency of the vehicle is far from the distance between adjacent points, which weakens the correlation between the points, making MM more difficult. In this paper, an MM algorithm based on priority rules is designed for vehicle trajectory characteristics at low sampling frequencies. Findings - The experimental results show that the MM based on priority rule algorithm can effectively match the trajectory data of low sampling frequency with the actual road, and the matching accuracy is better than other similar algorithms, the processing speed reaches 73 per second. Research limitations/implications - In the algorithm verification of this paper, although the algorithm design and experimental verification are considered considering the diversity of GPS data sampling frequency, the experimental data used are still a single source. Originality/value - Based on the GPS trajectory data of the Ministry of Transport, the experimental results show that the accuracy of the priority-based weight-based algorithm is higher. The accuracy of this algorithm is over 98.1 per cent, which is better than other similar algorithms.https://www.emerald.com/insight/content/doi/10.1108/IJCS-01-2019-0001/full/pdf?title=research-on-map-matching-algorithm-based-on-priority-rule-for-low-sampling-frequency-vehicle-navigation-dataalgorithmcrowdsourced big data and analytics |
| spellingShingle | Zhishuo Liu Yao Dongxin Zhao Kuan Wang Chun Fang Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data International Journal of Crowd Science algorithm crowdsourced big data and analytics |
| title | Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| title_full | Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| title_fullStr | Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| title_full_unstemmed | Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| title_short | Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| title_sort | research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| topic | algorithm crowdsourced big data and analytics |
| url | https://www.emerald.com/insight/content/doi/10.1108/IJCS-01-2019-0001/full/pdf?title=research-on-map-matching-algorithm-based-on-priority-rule-for-low-sampling-frequency-vehicle-navigation-data |
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