Gündling, Felix ; Hopp, Florian ; Weihe, Karsten (2024)
Efficient monitoring of public transport journeys.
In: Public Transport : Planning and Operations, 2020, 12 (3)
doi: 10.26083/tuprints-00024010
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Efficient monitoring of public transport journeys |
Language: | English |
Date: | 26 April 2024 |
Place of Publication: | Darmstadt |
Year of primary publication: | October 2020 |
Place of primary publication: | Berlin ; Heidelberg |
Publisher: | Springer |
Journal or Publication Title: | Public Transport : Planning and Operations |
Volume of the journal: | 12 |
Issue Number: | 3 |
DOI: | 10.26083/tuprints-00024010 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | Many things can go wrong on a journey. From minor disturbances like a track change to major problems like train cancellations, everything can happen. The broad availability of smartphones enables us to keep the traveler up-to-date with information relevant for the journey. This way, the traveler can react to changes as early as possible and make well-informed decisions. Naive approaches are too inefficient to monitor a large number of journeys in real-time. This paper presents an efficient way to monitor millions of journeys in parallel. In our approach, the selection of change notices to be communicated to a traveler may be flexibly adapted to the travelers individual needs. |
Uncontrolled Keywords: | Real-time, Public transport, Personalized, Connection monitoring |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-240108 |
Classification DDC: | 000 Generalities, computers, information > 004 Computer science 300 Social sciences > 380 Commerce, communications, transportation |
Divisions: | 20 Department of Computer Science > Algorithmics |
Date Deposited: | 26 Apr 2024 12:40 |
Last Modified: | 30 Apr 2024 06:57 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/24010 |
PPN: | 517598647 |
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