Volume

Dagstuhl Seminar Proceedings, Volume 10121

Publication Details

  • published at: 2010-08-06
  • Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik

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Document
DOI: 10.4230/DagSemProc.10121.1
10121 Abstracts Collection – Computational Transportation Science

Authors: Glenn Geers, Monika Sester, Stephan Winter, and Ouri Wolfson

Abstract
From 21.03. to 26.03.2010, the Dagstuhl Seminar 10121 ``Computational Transportation Science '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Glenn Geers, Monika Sester, Stephan Winter, and Ouri Wolfson. 10121 Abstracts Collection – Computational Transportation Science. In Computational Transportation Science. Dagstuhl Seminar Proceedings, Volume 10121, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{geers_et_al:DagSemProc.10121.1,
  author =	{Geers, Glenn and Sester, Monika and Winter, Stephan and Wolfson, Ouri},
  title =	{{10121 Abstracts Collection – Computational Transportation Science}},
  booktitle =	{Computational Transportation Science},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10121},
  editor =	{Glenn Geers and Monika Sester and Stephan Winter and Ouri E. Wolfson},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10121.1},
  URN =		{urn:nbn:de:0030-drops-27235},
  doi =		{10.4230/DagSemProc.10121.1},
  annote =	{Keywords: Computational Transportation Science}
}
Document
DOI: 10.4230/DagSemProc.10121.2
10121 Report – Towards a Computational Transportation Science

Authors: Glenn Geers, Monika Sester, Stephan Winter, and Ouri Wolfson

Abstract
In the near future, vehicles, travelers, and the infrastructure will collectively have billions of sensors that can communicate with each other. This environment will enable numerous novel applications and order of magnitude improvements in the performance of existing applications. However, information technology (IT) has not had the dramatic impact on day-to-day transportation that it has had on other domains such as business and science. In terms of the real-time information available to most travelers, with the exception of car navigation systems, the transportation experience has not changed much in the last 30-40 years. During this same time, the miniaturization of computing devices and advances in wireless communication and sensor technology have been propagating computing from the stationary desktop to the mobile outdoors, and making it ubiquitous. Future transportation systems, due to their distributed/mobile nature, can become the ultimate test-bed for this ubiquitous (i.e., embedded, highly-distributed, and sensor-laden) computing environment of unprecedented scale. Information technology is the foundation for implementing new transportation control and management strategies, particularly if they are to be made available in real-time to wireless devices such as cell phones and PDAs, traffic lights or dynamic signs. A related development is the emergence of increasingly more sophisticated geospatial (including spatiotemporal) information management capabilities.
Cite as

Glenn Geers, Monika Sester, Stephan Winter, and Ouri Wolfson. 10121 Report – Towards a Computational Transportation Science. In Computational Transportation Science. Dagstuhl Seminar Proceedings, Volume 10121, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{geers_et_al:DagSemProc.10121.2,
  author =	{Geers, Glenn and Sester, Monika and Winter, Stephan and Wolfson, Ouri},
  title =	{{10121 Report – Towards a  Computational Transportation Science}},
  booktitle =	{Computational Transportation Science},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10121},
  editor =	{Glenn Geers and Monika Sester and Stephan Winter and Ouri E. Wolfson},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10121.2},
  URN =		{urn:nbn:de:0030-drops-27222},
  doi =		{10.4230/DagSemProc.10121.2},
  annote =	{Keywords: Computational Transportation Science}
}
Document
DOI: 10.4230/DagSemProc.10121.3
Capacity Constrained Routing Algorithms for Evacuation Route Planning

Authors: Shashi Shekhar, Betsy George, and Qingsong Lu

Abstract
Efficient tools are needed to identify routes and schedules to evacuate affected populations to safety in face of natural disasters or terrorist attacks. Challenges arise due to violation of key assumptions (e.g. stationary ranking of alternative routes, Wardrop equilibrium) behind popular shortest path algorithms (e.g. Dijktra's, A*) and microscopic traffic simulators (e.g. DYNASMART). Time-expanded graphs (TEG) based mathematical programming paradigm does not scale up to large urban scenarios due to excessive duplication of transportation network across time-points. We present a new approach, namely Capacity Constrained Route Planner (CCRP), advancing ideas such as Time-Aggregated Graph (TAG) and an ATST function to provide earliest-Arrival-Time given any Start-Time. Laboratory experiments and field use in Twincities for DHS scenarios (e.g. Nuclear power plant, terrorism) show that CCRP is much faster than the state of the art. A key Transportation Science insight suggests that walking the first mile, when appropriate, may speed-up evacuation by a factor of 2 to 3 for many scenarios. Geographic Information Science (e.g. Time Geography) contributions include a novel representation (e.g. TAG) for spatio-temporal networks. Computer Science contributions include graph theory limitations (e.g. non-stationary ranking of routes, non-FIFO behavior) and scalable algorithms for traditional routing problems in time-varying networks, as well as new problems such as identifying the best start-time (for a given arrival-time deadline) to minimize travel-time.
Cite as

Shashi Shekhar, Betsy George, and Qingsong Lu. Capacity Constrained Routing Algorithms for Evacuation Route Planning. In Computational Transportation Science. Dagstuhl Seminar Proceedings, Volume 10121, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{shekhar_et_al:DagSemProc.10121.3,
  author =	{Shekhar, Shashi and George, Betsy and Lu, Qingsong},
  title =	{{Capacity Constrained Routing Algorithms for Evacuation Route Planning}},
  booktitle =	{Computational Transportation Science},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10121},
  editor =	{Glenn Geers and Monika Sester and Stephan Winter and Ouri E. Wolfson},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10121.3},
  URN =		{urn:nbn:de:0030-drops-27216},
  doi =		{10.4230/DagSemProc.10121.3},
  annote =	{Keywords: Evacuation, routes, spatio-temporal networks}
}

Filters

  • Authors
  • G
  • Geers, Glenn
  • George, Betsy
  • L
  • Lu, Qingsong
  • S
  • Sester, Monika
  • Shekhar, Shashi
  • W
  • Winter, Stephan
  • Wolfson, Ouri

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