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Documents authored by Dibbelt, Julian


Document
Faster Transit Routing by Hyper Partitioning

Authors: Daniel Delling, Julian Dibbelt, Thomas Pajor, and Tobias Zündorf

Published in: OASIcs, Volume 59, 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017)


Abstract
We present a preprocessing-based acceleration technique for computing bi-criteria Pareto-optimal journeys in public transit networks, based on the well-known RAPTOR algorithm [Delling et al 2015]. Our key idea is to first partition a hypergraph into cells, in which vertices correspond to routes (e.g., bus lines) and hyperedges to stops, and to then mark routes sufficient for optimal travel across cells. The query can then be restricted to marked routes and those in the source and target cells. This results in a practical approach, suitable for networks that are too large to be efficiently handled by the basic RAPTOR algorithm.

Cite as

Daniel Delling, Julian Dibbelt, Thomas Pajor, and Tobias Zündorf. Faster Transit Routing by Hyper Partitioning. In 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017). Open Access Series in Informatics (OASIcs), Volume 59, pp. 8:1-8:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)


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@InProceedings{delling_et_al:OASIcs.ATMOS.2017.8,
  author =	{Delling, Daniel and Dibbelt, Julian and Pajor, Thomas and Z\"{u}ndorf, Tobias},
  title =	{{Faster Transit Routing by Hyper Partitioning}},
  booktitle =	{17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017)},
  pages =	{8:1--8:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-042-2},
  ISSN =	{2190-6807},
  year =	{2017},
  volume =	{59},
  editor =	{D'Angelo, Gianlorenzo and Dollevoet, Twan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2017.8},
  URN =		{urn:nbn:de:0030-drops-78962},
  doi =		{10.4230/OASIcs.ATMOS.2017.8},
  annote =	{Keywords: Routing, speed-up techniques, public transport, partitioning}
}
Document
Modeling and Engineering Constrained Shortest Path Algorithms for Battery Electric Vehicles

Authors: Moritz Baum, Julian Dibbelt, Dorothea Wagner, and Tobias Zündorf

Published in: LIPIcs, Volume 87, 25th Annual European Symposium on Algorithms (ESA 2017)


Abstract
We study the problem of computing constrained shortest paths for battery electric vehicles. Since battery capacities are limited, fastest routes are often infeasible. Instead, users are interested in fast routes where the energy consumption does not exceed the battery capacity. For that, drivers can deliberately reduce speed to save energy. Hence, route planning should provide both path and speed recommendations. To tackle the resulting NP-hard optimization problem, previous work trades correctness or accuracy of the underlying model for practical running times. In this work, we present a novel framework to compute optimal constrained shortest paths for electric vehicles that uses more realistic physical models, while taking speed adaptation into account. Careful algorithm engineering makes the approach practical even on large, realistic road networks: We compute optimal solutions in less than a second for typical battery capacities, matching performance of previous inexact methods. For even faster performance, the approach can easily be extended with heuristics that provide high quality solutions within milliseconds.

Cite as

Moritz Baum, Julian Dibbelt, Dorothea Wagner, and Tobias Zündorf. Modeling and Engineering Constrained Shortest Path Algorithms for Battery Electric Vehicles. In 25th Annual European Symposium on Algorithms (ESA 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 87, pp. 11:1-11:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)


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@InProceedings{baum_et_al:LIPIcs.ESA.2017.11,
  author =	{Baum, Moritz and Dibbelt, Julian and Wagner, Dorothea and Z\"{u}ndorf, Tobias},
  title =	{{Modeling and Engineering Constrained Shortest Path Algorithms for Battery Electric Vehicles}},
  booktitle =	{25th Annual European Symposium on Algorithms (ESA 2017)},
  pages =	{11:1--11:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-049-1},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{87},
  editor =	{Pruhs, Kirk and Sohler, Christian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2017.11},
  URN =		{urn:nbn:de:0030-drops-78672},
  doi =		{10.4230/LIPIcs.ESA.2017.11},
  annote =	{Keywords: electric vehicles, constrained shortest paths, algorithm engineering}
}
Document
Towards Realistic Pedestrian Route Planning

Authors: Simeon Andreev, Julian Dibbelt, Martin Nöllenburg, Thomas Pajor, and Dorothea Wagner

Published in: OASIcs, Volume 48, 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015)


Abstract
Pedestrian routing has its specific set of challenges, which are often neglected by state-of-the-art route planners. For instance, the lack of detailed sidewalk data and the inability to traverse plazas and parks in a natural way often leads to unappealing and suboptimal routes. In this work, we first propose to augment the network by generating sidewalks based on the street geometry and adding edges for routing over plazas and squares. Using this and further information, our query algorithm seamlessly handles node-to-node queries and queries whose origin or destination is an arbitrary location on a plaza or inside a park. Our experiments show that we are able to compute appealing pedestrian routes at negligible overhead over standard routing algorithms.

Cite as

Simeon Andreev, Julian Dibbelt, Martin Nöllenburg, Thomas Pajor, and Dorothea Wagner. Towards Realistic Pedestrian Route Planning. In 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015). Open Access Series in Informatics (OASIcs), Volume 48, pp. 1-15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2015)


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@InProceedings{andreev_et_al:OASIcs.ATMOS.2015.1,
  author =	{Andreev, Simeon and Dibbelt, Julian and N\"{o}llenburg, Martin and Pajor, Thomas and Wagner, Dorothea},
  title =	{{Towards Realistic Pedestrian Route Planning}},
  booktitle =	{15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015)},
  pages =	{1--15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-99-6},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{48},
  editor =	{Italiano, Giuseppe F. and Schmidt, Marie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2015.1},
  URN =		{urn:nbn:de:0030-drops-54592},
  doi =		{10.4230/OASIcs.ATMOS.2015.1},
  annote =	{Keywords: pedestrian routing, realistic model, shortest paths, speed-up technique}
}
Document
Delay-Robust Journeys in Timetable Networks with Minimum Expected Arrival Time

Authors: Julian Dibbelt, Ben Strasser, and Dorothea Wagner

Published in: OASIcs, Volume 42, 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2014)


Abstract
We study the problem of computing delay-robust routes in timetable networks. Instead of a single path we compute a decision graph containing all stops and trains/vehicles that might be relevant. Delays are formalized using a stochastic model. We show how to compute a decision graph that minimizes the expected arrival time while bounding the latest arrival time over all sub-paths. Finally we show how the information contained within a decision graph can compactly be represented to the user. We experimentally evaluate our algorithms and show that the running times allow for interactive usage on a realistic train network.

Cite as

Julian Dibbelt, Ben Strasser, and Dorothea Wagner. Delay-Robust Journeys in Timetable Networks with Minimum Expected Arrival Time. In 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 42, pp. 1-14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2014)


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@InProceedings{dibbelt_et_al:OASIcs.ATMOS.2014.1,
  author =	{Dibbelt, Julian and Strasser, Ben and Wagner, Dorothea},
  title =	{{Delay-Robust Journeys in Timetable Networks with Minimum Expected Arrival Time}},
  booktitle =	{14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{1--14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-75-0},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{42},
  editor =	{Funke, Stefan and Mihal\'{a}k, Mat\'{u}s},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2014.1},
  URN =		{urn:nbn:de:0030-drops-47488},
  doi =		{10.4230/OASIcs.ATMOS.2014.1},
  annote =	{Keywords: Algorithms, Optimization, Delay-robustness, Route planning, Public transportation}
}
Document
Speed-Consumption Tradeoff for Electric Vehicle Route Planning

Authors: Moritz Baum, Julian Dibbelt, Lorenz Hübschle-Schneider, Thomas Pajor, and Dorothea Wagner

Published in: OASIcs, Volume 42, 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2014)


Abstract
We study the problem of computing routes for electric vehicles (EVs) in road networks. Since their battery capacity is limited, and consumed energy per distance increases with velocity, driving the fastest route is often not desirable and may even be infeasible. On the other hand, the energy-optimal route may be too conservative in that it contains unnecessary detours or simply takes too long. In this work, we propose to use multicriteria optimization to obtain Pareto sets of routes that trade energy consumption for speed. In particular, we exploit the fact that the same road segment can be driven at different speeds within reasonable intervals. As a result, we are able to provide routes with low energy consumption that still follow major roads, such as freeways. Unfortunately, the size of the resulting Pareto sets can be too large to be practical. We therefore also propose several nontrivial techniques that can be applied on-line at query time in order to speed up computation and filter insignificant solutions from the Pareto sets. Our extensive experimental study, which uses a real-world energy consumption model, reveals that we are able to compute diverse sets of alternative routes on continental networks that closely resemble the exact Pareto set in just under a second---several orders of magnitude faster than the exhaustive algorithm.

Cite as

Moritz Baum, Julian Dibbelt, Lorenz Hübschle-Schneider, Thomas Pajor, and Dorothea Wagner. Speed-Consumption Tradeoff for Electric Vehicle Route Planning. In 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 42, pp. 138-151, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2014)


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@InProceedings{baum_et_al:OASIcs.ATMOS.2014.138,
  author =	{Baum, Moritz and Dibbelt, Julian and H\"{u}bschle-Schneider, Lorenz and Pajor, Thomas and Wagner, Dorothea},
  title =	{{Speed-Consumption Tradeoff for Electric Vehicle Route Planning}},
  booktitle =	{14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{138--151},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-75-0},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{42},
  editor =	{Funke, Stefan and Mihal\'{a}k, Mat\'{u}s},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2014.138},
  URN =		{urn:nbn:de:0030-drops-47583},
  doi =		{10.4230/OASIcs.ATMOS.2014.138},
  annote =	{Keywords: electric vehicles, shortest paths, route planning, bicriteria optimization, algorithm engineering}
}
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