9 Search Results for "Urban, Marie"

Document
DOI: 10.4230/LIPIcs.ECOOP.2024.20
Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization

Authors: Florian Huemer, David Leopoldseder, Aleksandar Prokopec, Raphael Mosaner, and Hanspeter Mössenböck

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Improving compilation time in optimizing compilers is challenging due to their large number of interconnected components. This includes compiler optimizations, compiler tiers, heuristics, and profiling information. Despite this complexity, research in compilation-time optimization is often guided by analyzing metrics of entire program runs, such as the total compilation time and overall memory footprint. This coarse-grained perspective hides relevant information, such as source program functions for which the compiler allocates a lot of memory or compiler optimizations with a high impact on the total compilation time. This leaves high-level metrics as the only reference point for driving optimization design. Consequently, compilation-time regressions in one program function that are obscured by improvements in other functions stay undetected, while the impacts of compiler changes on untouched parts of the compiler are mainly unknown. Furthermore, developers overlook long-standing compiler defects because their high-level metrics do not change over time. To address these limitations, we propose ICON, a new data-driven approach to compilation-time optimization that breaks up high-level metrics into individual source program functions, compiler optimizations, or even into individual instructions in the compiler source code. Our methodology enables an iterative in-depth compilation-time analysis, focusing on outliers to identify optimization opportunities. We show that outliers, both in terms of time spent in a particular compiler optimization, and in terms of individual compilations that take substantially longer, can reveal potential problems in the compiler implementation. We applied our approach to GraalVM and extracted data for multiple of its language runtimes. We analyzed the resulting data, present the first detailed look into the distribution of compilation time in the GraalVM compiler, a state-of-the-art multi-language compiler, and identified defects that led to regressions in overall compilation time or the compilation time of specific languages. We furthermore designed two optimizations based on the identified outliers that improve compilation time between 2.25% and 9.45%. We believe that our approach can guide compiler developers in finding usually overlooked optimization potential and defects, and focus future research efforts in making compilers more efficient.
Cite as

Florian Huemer, David Leopoldseder, Aleksandar Prokopec, Raphael Mosaner, and Hanspeter Mössenböck. Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 20:1-20:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{huemer_et_al:LIPIcs.ECOOP.2024.20,
  author =	{Huemer, Florian and Leopoldseder, David and Prokopec, Aleksandar and Mosaner, Raphael and M\"{o}ssenb\"{o}ck, Hanspeter},
  title =	{{Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{20:1--20:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.20},
  URN =		{urn:nbn:de:0030-drops-208693},
  doi =		{10.4230/LIPIcs.ECOOP.2024.20},
  annote =	{Keywords: Compilation time, outliers, dynamic languages, virtual machines, GraalVM, ICON}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.6
Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?

Authors: Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Despite the frequent use of sketch maps in assessing environmental knowledge, it remains unclear how and to what degree familiarity impacts sketch map content. In the present study, we assess whether different levels of familiarity relate to differences in the content and spatial accuracy of environmental knowledge depicted in sketch maps drawn for the purpose of route instructions. To this end, we conduct a real-world wayfinding study with 91 participants, all of whom have to walk along a pre-defined route of approximately 2.3km length. Prior to the walk, we collect self-report familiarity ratings from participants for both a set of 15 landmarks and a set of areas we define as hexagons along the route. Once participants finished walking the route, they were asked to sketch a map of the route, specifically a sketch that would enable a person who had never walked the route to follow it. We found that participants unfamiliar with the areas along the route sketched fewer features than familiar people did. Contrary to our expectations, however, we found that landmarks were sketched or not regardless of participants' level of familiarity with the landmarks. We were also surprised that the level of familiarity was not correlated to the accuracy of the sketched order of features along the route, of the position of sketched features in relation to the route, nor to the metric locational accuracy of feature placement on the sketches. These results lead us to conclude that different aspects of feature salience influence whether the features are included on sketch maps, independent of familiarity. They also point to the influence of task context on the content of sketch maps, again independent of familiarity. We propose further studies to more fully explore these ideas.
Cite as

Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos. Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kattenbeck_et_al:LIPIcs.COSIT.2024.6,
  author =	{Kattenbeck, Markus and Montello, Daniel R. and Raubal, Martin and Giannopoulos, Ioannis},
  title =	{{Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{6:1--6:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.6},
  URN =		{urn:nbn:de:0030-drops-208215},
  doi =		{10.4230/LIPIcs.COSIT.2024.6},
  annote =	{Keywords: Familiarity, Spatial Knowledge, Sketch Maps}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.26
Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings (Short Paper)

Authors: Crystal J. Bae, Lydia Wileden, and Emily Talen

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
The idea of the urban neighborhood has long been of interest to residents, planners, and scholars. We describe a project focused on Chicago neighborhood mapping and pose related questions about the analysis of crowdsourced neighborhood boundary drawings. To gain insight into Chicago residents’ cognitive maps and the relationship between those internal representations and existing administrative boundaries, the authors launched the Chicago Neighborhood Project (CNP), which invited Chicago residents to draw their own and other neighborhoods within the city using an online mapping interface. The goal of CNP is to examine variation in how neighborhoods are defined by residents and use that variation to inform how policymakers, planners, and researchers create, implement, and measure place-based policies. Because the project had a goal of collecting a large sample of neighborhood map drawings, the project took a crowdsourced approach, recruiting responses via email to community groups, social media, targeted web advertisements, flyering, collaborations with news media, and word of mouth. This paper describes our data collection methodology, resulting in over 5,000 responses, as well as decisions related to initial data cleaning and analysis. We present early findings from the project in relation to understanding Chicago residents' cognitive boundaries of the "neighborhood." TL;DR: We present preliminary results of the Chicago Neighborhood Project (CNP), which collected over 5,000 drawings of neighborhood areas from residents, making it the largest such effort to elicit an understanding of neighborhood regions in Chicago.
Cite as

Crystal J. Bae, Lydia Wileden, and Emily Talen. Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 26:1-26:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{bae_et_al:LIPIcs.COSIT.2024.26,
  author =	{Bae, Crystal J. and Wileden, Lydia and Talen, Emily},
  title =	{{Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{26:1--26:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.26},
  URN =		{urn:nbn:de:0030-drops-208419},
  doi =		{10.4230/LIPIcs.COSIT.2024.26},
  annote =	{Keywords: cognitive regions, urban neighborhoods, boundary mapping, sketch mapping}
}
Document
DOI: 10.4230/DagMan.10.1.1
Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282)

Authors: James P. Delgrande, Birte Glimm, Thomas Meyer, Miroslaw Truszczynski, and Frank Wolter

Published in: Dagstuhl Manifestos, Volume 10, Issue 1 (2024)

Abstract
Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022,sser a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade.
Cite as

James P. Delgrande, Birte Glimm, Thomas Meyer, Miroslaw Truszczynski, and Frank Wolter. Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282). In Dagstuhl Manifestos, Volume 10, Issue 1, pp. 1-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{delgrande_et_al:DagMan.10.1.1,
  author =	{Delgrande, James P. and Glimm, Birte and Meyer, Thomas and Truszczynski, Miroslaw and Wolter, Frank},
  title =	{{Current and Future Challenges in Knowledge Representation and Reasoning (Dagstuhl Perspectives Workshop 22282)}},
  pages =	{1--61},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2024},
  volume =	{10},
  number =	{1},
  editor =	{Delgrande, James P. and Glimm, Birte and Meyer, Thomas and Truszczynski, Miroslaw and Wolter, Frank},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.10.1.1},
  URN =		{urn:nbn:de:0030-drops-201403},
  doi =		{10.4230/DagMan.10.1.1},
  annote =	{Keywords: Knowledge representation and reasoning, Applications of logics, Declarative representations, Formal logic}
}
Document
Position
DOI: 10.4230/TGDK.2.1.2
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.
Cite as

Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.3
Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians

Authors: Christina Ludwig, Sven Lautenbach, Eva-Marie Schömann, and Alexander Zipf

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II

Abstract
Routes with a high share of greenery are attractive for cyclist and pedestrians. We analyze how strongly such green routes differ from the respective fast routes using the openrouteservice. Greenness of streets was estimated based on OpenStreetMap data in combination with Sentinel-II imagery, 3d laser scan data and administrative information on trees on public ground. We assess the effect both at the level of the individual route and at the urban level for two German cities: Dresden and Heidelberg. For individual routes, we study how strongly green routes differ from the respective fast routes. In addition, we identify parts of the road network which represent important green corridors as well as unattractive parts which can or cannot be avoided at the cost of reasonable detours. In both cities, our results show the importance of urban green spaces for the provision of attractive green routes and provide new insights for urban planning by identifying unvegetated bottlenecks in the street network for which no green alternatives exist at this point.
Cite as

Christina Ludwig, Sven Lautenbach, Eva-Marie Schömann, and Alexander Zipf. Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ludwig_et_al:LIPIcs.GIScience.2021.II.3,
  author =	{Ludwig, Christina and Lautenbach, Sven and Sch\"{o}mann, Eva-Marie and Zipf, Alexander},
  title =	{{Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.3},
  URN =		{urn:nbn:de:0030-drops-147622},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.3},
  annote =	{Keywords: Routing, OpenStreetMap, route choice, urban vegetation, sustainable mobility}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.58
Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper)

Authors: Kelly Sims, Gautam Thakur, Kevin Sparks, Marie Urban, Amy Rose, and Robert Stewart

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
Geo-grid algorithms divide a large polygon area into several smaller polygons, which are important for studying or executing a set of operations on underlying topological features of a map. The current geo-grid algorithms divide a large polygon in to a set of smaller but equal size polygons only (e.g. is ArcMaps Fishnet). The time to create a geo-grid is typically proportional to number of smaller polygons created. This raises two problems - (i) They cannot skip unwanted areas (such as water bodies, given about 71% percent of the Earth's surface is water-covered); (ii) They are incognizant to any underlying feature set that requires more deliberation. In this work, we propose a novel dynamically spaced geo-grid segmentation algorithm that overcomes these challenges and provides a computationally optimal output for borderline cases of an uneven polygon. Our method uses an underlying topological feature of population distributions, from the LandScan Global 2016 dataset, for creating grids as a function of these weighted features. We benchmark our results against available algorithms and found our approach improves geo-grid creation. Later on, we demonstrate the proposed approach is more effective in harvesting Points of Interest data from a crowd-sourced platform.
Cite as

Kelly Sims, Gautam Thakur, Kevin Sparks, Marie Urban, Amy Rose, and Robert Stewart. Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 58:1-58:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{sims_et_al:LIPIcs.GISCIENCE.2018.58,
  author =	{Sims, Kelly and Thakur, Gautam and Sparks, Kevin and Urban, Marie and Rose, Amy and Stewart, Robert},
  title =	{{Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{58:1--58:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.58},
  URN =		{urn:nbn:de:0030-drops-93860},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.58},
  annote =	{Keywords: geofence, geo-grid, quadtree, points of interest (POI), volunteered geographic information (VGI)}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2015.16
Speedups for Multi-Criteria Urban Bicycle Routing

Authors: Jan Hrncir, Pavol Zilecky, Qing Song, and Michal Jakob

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

Abstract
Increasing the adoption of cycling is crucial for achieving more sustainable urban mobility. Navigating larger cities on a bike is, however, often challenging due to cities’ fragmented cycling infrastructure and/or complex terrain topology. Cyclists would thus benefit from intelligent route planning that would help them discover routes that best suit their transport needs and preferences. Because of the many factors cyclists consider in deciding their routes, employing multi-criteria route search is vital for properly accounting for cyclists’ route-choice criteria. Direct application of optimal multi-criteria route search algorithms is, however, not feasible due to their prohibitive computational complexity. In this paper, we therefore propose several heuristics for speeding up multi-criteria route search. We evaluate our method on a real-world cycleway network and show that speedups of up to four orders of magnitude over the standard multi-criteria label-setting algorithm are possible with a reasonable loss of solution quality. Our results make it possible to practically deploy bicycle route planners capable of producing high-quality route suggestions respecting multiple real-world route-choice criteria.
Cite as

Jan Hrncir, Pavol Zilecky, Qing Song, and Michal Jakob. Speedups for Multi-Criteria Urban Bicycle Routing. In 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015). Open Access Series in Informatics (OASIcs), Volume 48, pp. 16-28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{hrncir_et_al:OASIcs.ATMOS.2015.16,
  author =	{Hrncir, Jan and Zilecky, Pavol and Song, Qing and Jakob, Michal},
  title =	{{Speedups for Multi-Criteria Urban Bicycle Routing}},
  booktitle =	{15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015)},
  pages =	{16--28},
  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.2015.16},
  URN =		{urn:nbn:de:0030-drops-54584},
  doi =		{10.4230/OASIcs.ATMOS.2015.16},
  annote =	{Keywords: bicycle routing, multi-criteria shortest path, heuristic speedups}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2015.68
Robust Routing in Urban Public Transportation: Evaluating Strategies that Learn From the Past

Authors: Katerina Böhmová, Matúš Mihalák, Peggy Neubert, Tobias Pröger, and Peter Widmayer

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

Abstract
Given an urban public transportation network and historic delay information, we consider the problem of computing reliable journeys. We propose new algorithms based on our recently presented solution concept (Böhmová et al., ATMOS 2013), and perform an experimental evaluation using real-world delay data from Zürich, Switzerland. We compare these methods to natural approaches as well as to our recently proposed method which can also be used to measure typicality of past observations. Moreover, we demonstrate how this measure relates to the predictive quality of the individual methods. In particular, if the past observations are typical, then the learning- based methods are able to produce solutions that perform well on typical days, even in the presence of large delays.
Cite as

Katerina Böhmová, Matúš Mihalák, Peggy Neubert, Tobias Pröger, and Peter Widmayer. Robust Routing in Urban Public Transportation: Evaluating Strategies that Learn From the Past. In 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015). Open Access Series in Informatics (OASIcs), Volume 48, pp. 68-81, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{bohmova_et_al:OASIcs.ATMOS.2015.68,
  author =	{B\"{o}hmov\'{a}, Katerina and Mihal\'{a}k, Mat\'{u}\v{s} and Neubert, Peggy and Pr\"{o}ger, Tobias and Widmayer, Peter},
  title =	{{Robust Routing in Urban Public Transportation: Evaluating Strategies that Learn From the Past}},
  booktitle =	{15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015)},
  pages =	{68--81},
  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.2015.68},
  URN =		{urn:nbn:de:0030-drops-54542},
  doi =		{10.4230/OASIcs.ATMOS.2015.68},
  annote =	{Keywords: public transportation, route planning, robustness, optimization, experiments}
}
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