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Open AccessArticle

Multimodal Dynamic Journey-Planning

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Computer Technology Institute and Press “Diophantus”, 26504 Patras, Greece
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Department of Computer Engineering & Informatics, University of Patras, 26504 Patras, Greece
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Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the 23rd IEEE Symposium on Computers and Communications (ISCC), Natal, Brazil, 25–28 June 2018.
Algorithms 2019, 12(10), 213; https://doi.org/10.3390/a12100213
Received: 13 July 2019 / Revised: 9 October 2019 / Accepted: 10 October 2019 / Published: 13 October 2019
In this paper, a new model, known as the multimodal dynamic timetable model (DTM), is presented for computing optimal multimodal journeys in schedule-based public transport systems. The new model constitutes an extension of the dynamic timetable model (DTM), which was developed originally for a different setting (unimodal journey-planning). Multimodal DTM demonstrates a very fast query algorithm that meets the requirement for real-time response to best journey queries, and an ultra-fast update algorithm for updating the timetable information in case of delays of scheduled-based vehicles. An experimental study on real-world metropolitan networks demonstrates that the query and update algorithms of Multimodal DTM compare favorably with other state-of-the-art approaches when public transport, including unrestricted—with respect to departing time—traveling (e.g., walking and electric vehicles) is considered. View Full-Text
Keywords: multimodal journey; dynamic timetable model; timetable update multimodal journey; dynamic timetable model; timetable update
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Giannakopoulou, K.; Paraskevopoulos, A.; Zaroliagis, C. Multimodal Dynamic Journey-Planning. Algorithms 2019, 12, 213.

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