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Intelligent Offloading Distribution of High Definition Street Maps for Highly Automated Vehicles

  • Conference paper
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Smart Cities, Green Technologies, and Intelligent Transport Systems (SMARTGREENS 2017, VEHITS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 921))

  • 867 Accesses

Abstract

Highly automated vehicles will change our personal mobility in the future. To ensure the safety and the comfort of their passengers, the cars have to rely on as many information regarding their current surrounding traffic situation, as they can obtain. In addition to classical sensors like cameras or radar sensors, automated vehicles use data from a so called High Definition Street Map. Through such maps, the vehicles are provided with continuous updates regarding their future driving environment on a centimeter accurate level. The required amount of data, which is necessary therefore, motivates the development of more efficient data transmission concepts. In this paper we present HD-Wmapan extension of our previous work the Dynamic Map Update Protocol. Based on each vehicle’s current context the Dynamic Map Update Protocol achieves a highly data efficient transmission of map updates compared to existing distribution approaches. HD-Wmapfurther reduces the costs of such transmissions by enabling map data to be shared via ad hoc communication between the vehicles. To evaluate the capabilities of HD-Wmapwe perform a first simulation of the morning commuting traffic within the area of Cologne, Germany. In this scenario HD-Wmapachieved an ad hoc map data off loading quota from cellular networks of up to 25.5%. These results demonstrate the gains of our approach to realize efficient map distribution via ad hoc communication, releasing load from wireless Internet access networks.

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Notes

  1. 1.

    http://uk.support.tomtom.com/app/content/id/9/locale/en_gb/page/4.

  2. 2.

    https://maps.google.de/.

  3. 3.

    https://www.postgresql.org/.

  4. 4.

    http://www.etsi.org/.

  5. 5.

    https://www.openstreetmap.org/.

  6. 6.

    http://sumo.dlr.de/wiki/Data/Scenarios/TAPASCologne.

  7. 7.

    http://sumo.dlr.de/.

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Author information

Authors and Affiliations

  1. Adam Opel AG, Bahnhofsplatz, 65423, Rüsselsheim, Hessen, Germany

    Florian Jomrich

  2. Department of Computer Science, UiT: The Arctic University of Norway, Hansine Hansens veg 54 Breivika, 9019, Tromsø, Norway

    Aakash Sharma

  3. KOM Multimedia Communications Lab, Technical University of Darmstadt, Rundeturmstr. 10, 64283, Darmstadt, Hessen, Germany

    Florian Jomrich, Tobias Rückelt, Doreen Böhnstedt & Ralf Steinmetz

Authors
  1. Florian Jomrich
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  2. Aakash Sharma
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  3. Tobias Rückelt
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  4. Doreen Böhnstedt
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  5. Ralf Steinmetz
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Corresponding author

Correspondence to Florian Jomrich .

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Editors and Affiliations

  1. Innovation Value Institute, National University of Ireland, Maynooth, Maynooth, Ireland

    Brian Donnellan

  2. Siemens Corporate Technology, Munich, Germany

    Cornel Klein

  3. School of Computing, Dublin City University, Dublin, Ireland

    Markus Helfert

  4. Ford Research and Advanced Engineering, Dearborn, MI, USA

    Oleg Gusikhin

  5. University of Lisbon, Lisbon, Portugal

    António Pascoal

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Jomrich, F., Sharma, A., Rückelt, T., Böhnstedt, D., Steinmetz, R. (2019). Intelligent Offloading Distribution of High Definition Street Maps for Highly Automated Vehicles. In: Donnellan, B., Klein, C., Helfert, M., Gusikhin, O., Pascoal, A. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. SMARTGREENS VEHITS 2017 2017. Communications in Computer and Information Science, vol 921. Springer, Cham. https://doi.org/10.1007/978-3-030-02907-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-02907-4_11

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