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Smart Information Systems pp 345–368Cite as

Intermodal Mobility Assistance for Megacities

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Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

In this chapter, we present an approach to utilize means of transportation in a more effective and sustainable fashion in order to increase the quality of life in cities and to contribute to global environmental objectives. We describe a travel assistance system that proposes intermodal traveling options which are tailored to drivers’ needs. Different information channels are integrated in the system. One of these channels is information derived from video analysis. This analysis is based on a macroscopic approach using particular features extracted from video snapshots periodically captured from static traffic surveillance cameras. The video analysis approach is evaluated on 254 highway traffic videos of the UCSD dataset and achieves an accuracy of 94.90 %. Finally, running at 15 frames per second on average, the approach is also appropriate for real-time video analysis, without requiring a special purpose computer. In addition, a routing system based on a dynamically changing map has been developed in order to provide fast and reliable routing solutions. It integrates the information from all channels into one world view and takes these into account when searching for routes through a city.

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Notes

  1. 1.

    Global Positioning System.

  2. 2.

    Bing Maps Website: http://www.bing.com/maps/.

  3. 3.

    XML is the abbreviation for Extensible Markup Language.

  4. 4.

    The Apache Xerces Project website: http://xerces.apache.org/.

  5. 5.

    More precisely, retrieving a street name has a time complexity in \(O(l)\), where \(l\) is the number of characters in the longest street name.

  6. 6.

    Internet Engineering Task Force website: http://tools.ietf.org/html/rfc6455/.

  7. 7.

    http://opencv.org/opencv-java-api.html.

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Acknowledgments

This work is funded by the Federal Ministry of Education and Research (BMBF) under funding reference number 01IS12049.

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Authors and Affiliations

  1. Technische Universität Berlin, Berlin, Germany

    Esra Acar, Marco Lützenberger & Marius Schulz

Authors
  1. Esra Acar
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  2. Marco Lützenberger
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  3. Marius Schulz
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Corresponding author

Correspondence to Esra Acar .

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Editors and Affiliations

  1. Technische Universität Berlin, Germany

    Frank Hopfgartner

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Acar, E., Lützenberger, M., Schulz, M. (2015). Intermodal Mobility Assistance for Megacities. In: Hopfgartner, F. (eds) Smart Information Systems. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-14178-7_13

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  • DOI: https://doi.org/10.1007/978-3-319-14178-7_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14177-0

  • Online ISBN: 978-3-319-14178-7

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