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Related papers: Fast and Delay-Robust Multimodal Journey Planning

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We study a multimodal journey planning scenario consisting of a public transit network and a transfer graph which represents a secondary transportation mode (e.g., walking, cycling, e-scooter). The objective is to compute Pareto-optimal…

Data Structures and Algorithms · Computer Science 2023-02-02 Moritz Baum , Valentin Buchhold , Jonas Sauer , Dorothea Wagner , Tobias Zündorf

State-of-the-art multimodal journey-planning algorithms, such as ULTRA, have recently been adapted to account for delays. In this work, we extend this approach to be more memory-efficient, faster, and accurate. We also adapt this framework…

Data Structures and Algorithms · Computer Science 2026-05-18 Denys Katkalo , Andrii Rohovyi , Toby Walsh

We study the problem of computing public transit traffic assignments in a multi-modal setting: Given a public transit timetable, an additional unrestricted transfer mode (in our case walking), and a set of origin-destination pairs, we aim…

Data Structures and Algorithms · Computer Science 2019-09-19 Jonas Sauer , Dorothea Wagner , Tobias Zündorf

We study the journey planning problem for multimodal networks consisting of public transit and a non-schedule-based transfer mode (e.g., walking, bicycle, e-scooter). So far, all efficient algorithms for this problem either restrict usage…

Data Structures and Algorithms · Computer Science 2021-10-26 Moritz Potthoff , Jonas Sauer

We study the problem of planning Pareto-optimal journeys in public transit networks. Most existing algorithms and speed-up techniques work by computing subjourneys to intermediary stops until the destination is reached. In contrast, the…

Data Structures and Algorithms · Computer Science 2016-09-16 Sascha Witt

Routing algorithms for public transport, particularly the widely used RAPTOR and its variants, often face performance bottlenecks during the transfer relaxation phase, especially on dense transfer graphs, when supporting unlimited…

Data Structures and Algorithms · Computer Science 2026-05-27 Andrii Rohovyi , Abdallah Abuaisha , Toby Walsh

We present multimodal DTM, a new model for multimodal journey planning in public (schedule-based) transport networks. Multimodal DTM constitutes an extension of the dynamic timetable model (DTM), developed originally for unimodal journey…

Data Structures and Algorithms · Computer Science 2018-04-17 Kalliopi Giannakopoulou , Andreas Paraskevopoulos , Christos Zaroliagis

We study the problem of computing all Pareto-optimal journeys in a public transit network regarding the two criteria of arrival time and number of transfers taken. We take a novel approach, focusing on trips and transfers between them,…

Data Structures and Algorithms · Computer Science 2016-07-06 Sascha Witt

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide…

Data Structures and Algorithms · Computer Science 2015-04-21 Hannah Bast , Daniel Delling , Andrew Goldberg , Matthias Müller-Hannemann , Thomas Pajor , Peter Sanders , Dorothea Wagner , Renato F. Werneck

We present T-REX (Transfer-Ranked EXploration), a new algorithm for journey planning in public transit networks on the country and continental scale. Our algorithm applies the principles of multi-level overlays to Trip-Based Public Transit…

Social and Information Networks · Computer Science 2026-05-20 Jonas Sauer , Patrick Steil , Sascha Witt

Train delays can propagate rapidly throughout the Urban Rail Transit (URT) network under networked operation conditions, posing significant challenges to operational departments. Accurately predicting passenger travel choices under train…

Machine Learning · Computer Science 2024-10-02 Chen Chen , Yuxin He , Hao Wang , Jingjing Chen , Qin Luo

Public transport administrators rely on efficient algorithms for various problems that arise in public transport networks. In particular, our study focused on designing linear-time algorithms for two fundamental path problems: the earliest…

Data Structures and Algorithms · Computer Science 2024-05-01 Mithinti Srikanth , G. Ramakrishna

We study the journey planning problem in public transit networks. Developing efficient preprocessing-based speedup techniques for this problem has been challenging: current approaches either require massive preprocessing effort or provide…

Data Structures and Algorithms · Computer Science 2015-05-07 Daniel Delling , Julian Dibbelt , Thomas Pajor , Renato F. Werneck

We study the problem of computing all Pareto-optimal journeys in a public transit network regarding the two criteria of arrival time and number of transfers taken. In recent years, great advances have been made in making public transit…

Data Structures and Algorithms · Computer Science 2021-09-30 Sascha Witt

Public transport routing plays a crucial role in transit network design, ensuring a satisfactory level of service for passengers. However, current routing solutions rely on traditional operational research heuristics, which can be…

Artificial Intelligence · Computer Science 2023-08-25 Nadav Shalit , Michael Fire , Dima Kagan , Eran Ben-Elia

Delays in public transport are common, often impacting users through prolonged travel times and missed transfers. Existing solutions for handling delays remain limited; backup plans based on historical data miss opportunities for earlier…

Artificial Intelligence · Computer Science 2025-05-21 Abdallah Abuaisha , Bojie Shen , Daniel Harabor , Peter Stuckey , Mark Wallace

Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment which are not able to capture many cross-segment complex factors, or…

Machine Learning · Computer Science 2018-02-08 Hanyuan Zhang , Hao Wu , Weiwei Sun , Baihua Zheng

Transit agencies that operate on-demand transportation services have to respond to trip requests from passengers in real time, which involves solving dynamic vehicle routing problems with pick-up and drop-off constraints. Based on…

Artificial Intelligence · Computer Science 2026-03-11 Amutheezan Sivagnanam , Ayan Mukhopadhyay , Samitha Samaranayake , Abhishek Dubey , Aron Laszka

Different passenger demand rates in transit stations underscore the importance of adopting operational strategies to provide a demand-responsive service. Aiming at improving passengers' travel time, the present study introduces an advanced…

Machine Learning · Computer Science 2022-09-08 Mohammadjavad Javadinasr , Amir Bahador Parsa , Abolfazl , Mohammadian

In urban settings, bus transit stands as a significant mode of public transportation, yet faces hurdles in delivering accurate and reliable arrival times. This discrepancy often culminates in delays and a decline in ridership, particularly…

Machine Learning · Computer Science 2024-03-05 Narges Rashvand , Sanaz Sadat Hosseini , Mona Azarbayjani , Hamed Tabkhi
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