Unified Occupancy on a Public Transport Network through Combination of AFC and APC Data
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913263892037632 |
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| author | Dib, Amir Cherrier, Noëlie Graive, Martin Rérolle, Baptiste Schmitt, Eglantine |
| author_facet | Dib, Amir Cherrier, Noëlie Graive, Martin Rérolle, Baptiste Schmitt, Eglantine |
| contents | In a transport network, the onboard occupancy is key for gaining insights into travelers' habits and adjusting the offer. Traditionally, operators have relied on field studies to evaluate ridership of a typical workday. However, automated fare collection (AFC) and automatic passenger counting (APC) data, which provide complete temporal coverage, are often available but underexploited. It should be noted, however, that each data source comes with its own biases: AFC data may not account for fraud, while not all vehicles are equipped with APC systems.
This paper introduces the unified occupancy method, a geostatistical model to extrapolate occupancy to every course of a public transportation network by combining AFC and APC data with partial coverage. Unified occupancy completes missing APC information for courses on lines where other courses have APC measures, as well as for courses on lines where no APC data is available at all. The accuracy of this method is evaluated on real data from several public transportation networks in France. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_05546 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unified Occupancy on a Public Transport Network through Combination of AFC and APC Data Dib, Amir Cherrier, Noëlie Graive, Martin Rérolle, Baptiste Schmitt, Eglantine Computers and Society Computational Engineering, Finance, and Science Machine Learning Applications In a transport network, the onboard occupancy is key for gaining insights into travelers' habits and adjusting the offer. Traditionally, operators have relied on field studies to evaluate ridership of a typical workday. However, automated fare collection (AFC) and automatic passenger counting (APC) data, which provide complete temporal coverage, are often available but underexploited. It should be noted, however, that each data source comes with its own biases: AFC data may not account for fraud, while not all vehicles are equipped with APC systems. This paper introduces the unified occupancy method, a geostatistical model to extrapolate occupancy to every course of a public transportation network by combining AFC and APC data with partial coverage. Unified occupancy completes missing APC information for courses on lines where other courses have APC measures, as well as for courses on lines where no APC data is available at all. The accuracy of this method is evaluated on real data from several public transportation networks in France. |
| title | Unified Occupancy on a Public Transport Network through Combination of AFC and APC Data |
| topic | Computers and Society Computational Engineering, Finance, and Science Machine Learning Applications |
| url | https://arxiv.org/abs/2403.05546 |