| Title: |
Research on map matching algorithm based on priority rule for low sampling frequency vehicle navigation data |
| Authors: |
Zhishuo Liu; Yao Dongxin; Zhao Kuan; Wang Chun Fang |
| Source: |
International Journal of Crowd Science, Vol 3, Iss 1, Pp 2-13 (2019) |
| Publisher Information: |
Tsinghua University Press |
| Publication Year: |
2019 |
| Collection: |
Directory of Open Access Journals: DOAJ Articles |
| Subject Terms: |
algorithm; crowdsourced big data and analytics; Technology; Engineering (General). Civil engineering (General); TA1-2040 |
| 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. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://doaj.org/toc/2398-7294; https://doaj.org/article/edb532f5c790420bbc5692a19c442e62 |
| DOI: |
10.1108/IJCS-01-2019-0001 |
| Availability: |
https://doi.org/10.1108/IJCS-01-2019-0001; https://doaj.org/article/edb532f5c790420bbc5692a19c442e62 |
| Accession Number: |
edsbas.F6F4E22D |
| Database: |
BASE |