RAILDASH: A DASHBOARD SYSTEM TO ANALYZE EFFECTS OF EVENTS ON RAILWAY TRAFFIC USING BIG GPS DATA

Autor: P. Jeph, H. Takayasu, T. Xia, H. Kanasugi, R. Jiang, H. Mizuseki, R. Shibasaki
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-4-W3-2022, Pp 89-96 (2022)
Druh dokumentu: article
ISSN: 2194-9042
2194-9050
DOI: 10.5194/isprs-annals-X-4-W3-2022-89-2022
Popis: The big events cause substantial deviations in the city traffic, especially railway transportation which happens to be the dominant mode of transportation for most of the major cities. Analysis of big events’ impact on railway transportation, therefore, is of great importance to urban planning and transport management, yet is quite challenging because of the lack of readily available data about railway passengers’ citywide flow and event participants’ choice of transportation mode. Previous works have mainly relied on precise but limited data like sensors, AFC (Automated Fare Collection), or smart-card get-on get-off data to estimate the railway passengers, and did not take a holistic multi-dimensional approach to analyze railway traffic congestion caused by the events. To tackle these challenges, we propose a novel interactive Dashboard system that utilizes millions of smartphone GPS records across Japan. The dashboard can estimate and visualize railway passengers for the stations nearby the event venue as well as other relevant event participants’ information. We also introduce a Congestion Index to measure the increase in congestion of stations during events. The dashboard can be highly useful for event organizers, railway administrators, and city planners to assess and compare the impact of big events on railway traffic.
Databáze: Directory of Open Access Journals