Algorithmic Analysis of GTFS-RT vehicle position accuracy
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866915331886284800 |
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| author | Wong, Joshua |
| author_facet | Wong, Joshua |
| contents | This paper presents three novel algorithms for calculating geodesic intersections on an ellipsoid. These algorithms are applied in a case study analyzing real-time transit data in California to assess vehicle position drift. The analysis reveals that while certain data anomalies can be corrected, large-scale discrepancies persist. The paper concludes by proposing a set of practical solutions that can be implemented by either data producers or consumers to significantly improve positional accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_06479 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Algorithmic Analysis of GTFS-RT vehicle position accuracy Wong, Joshua Geophysics This paper presents three novel algorithms for calculating geodesic intersections on an ellipsoid. These algorithms are applied in a case study analyzing real-time transit data in California to assess vehicle position drift. The analysis reveals that while certain data anomalies can be corrected, large-scale discrepancies persist. The paper concludes by proposing a set of practical solutions that can be implemented by either data producers or consumers to significantly improve positional accuracy. |
| title | Algorithmic Analysis of GTFS-RT vehicle position accuracy |
| topic | Geophysics |
| url | https://arxiv.org/abs/2506.06479 |