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Towards Dynamic and Flexible Sensor Fusion for Automotive Applications

  • Susana Alcalde BagüésEmail author
  • Wendelin Feiten
  • Tim Tiedemann
  • Christian Backe
  • Dhiraj Gulati
  • Steffen Lorenz
  • Peter Conradi
Conference paper
Part of the Lecture Notes in Mobility book series (LNMOB)

Abstract

In this paper we describe the concept of the data fusion and system architecture to be implemented in the collaborative research project Smart Adaptive Data Aggregation (SADA). The objective of SADA is to develop technologies that enable linking data from distributed mobile on-board sensors (on vehicles) with data from previously unknown stationary (e.g., infrastructure) or mobile sensors (e.g., other vehicles, smart devices). Data not only can be processed locally in the car, but also can be collected in a central backend, to allow machine learning based inference of additional information (enabling so-called crowd sensing). Ideally, crowd sensing might provide virtual sensors that could be used in the SADA fusion process.

Keywords

Data fusion Automotive applications Sensor crowd Car-To-X 

Notes

Acknowledgments

This work was partly funded by the Federal Republic of Germany, Ministry for Economic Affairs and Energy within the program ‘IKT EM III’, grant no. 01ME14002A.

References

  1. 1.
    Fecher N, Hoffmann J, Winner H, Fuchs K, Abendroth B, Bruder R (2009) “Aktive Gefahrenbremsungen”, ATZ – Automobiltechnische Zeitschrift, pp 140–146Google Scholar
  2. 2.
    http://www.aktiv-online.org. Accessed 02 May 2016
  3. 3.
    Toulminet G, Boussuge J, Laurgeau C (2008) Comparative synthesis of the 3 main European projects dealing with cooperative systems (cvis, safespot and coopers) and description of coopers demonstration site 4. In: 11th International IEEE conference on intelligent transportation systems, pp 809–814Google Scholar
  4. 4.
    Ko-FAS-website, see http://www.kofas.de. Accessed 02 May 2016
  5. 5.
    IEEE 802.11p, see https://standards.ieee.org. Accessed 28 May 2016
  6. 6.
    DRIVE-C2X-website. http://http://www.drive-c2x.eu. Accessed 02 May 2016
  7. 7.
    Dokic J, Müller B, Meyer G (2015) European roadmap smart systems for automated driving. Eur Technol Platform Smart Syst IntegrGoogle Scholar
  8. 8.
    Weiß C (2008) V2X communication in Europe from research projects towards standardization and field testing of vehicle communication technology. Comput Netw 55:3103–3119CrossRefGoogle Scholar
  9. 9.
    CONVERGE-website. http://converge-online.de. Accessed 02 May 2016
  10. 10.
    Duchrow T, Schröer M, Griesbach B, Kasperski S, Maas genannt Bermpohl F, Kramer S, Kirchner F (2012) Towards electric mobility data mining. In: 2012 IEEE International electric vehicle conference (IEVC), pp 1–6Google Scholar
  11. 11.
    Tiedemann T, Backe C, Vögele T, Conradi P (2016) An automotive distributed mobile sensor data collection with machine learning based data fusion and analysis on a central backend system. In: Proceedings of the 3rd International conference on system-integrated intelligence. Accepted, to be published in SysInt 2016Google Scholar
  12. 12.
    Tiedemann T, Vögele T, Krell MM, Metzen JH, Kirchner F (2015) Concept of a data thread based parking space occupancy prediction in a Berlin pilot region. In: Papers from the 2015 AAAI Workshop (WAIT-2015), AAAI PressGoogle Scholar
  13. 13.
    ROS, http://www.ros.org/. Accessed 28 May 2016
  14. 14.
    Nerurkar ED, Roumeliotis SI, Martinelli A (2009) Distributed maximum a posteriori estimation for multi-robot cooperative localization. In: IEEE International conference on robotics and automation, ICRA ’09, pp 1402–1409Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Susana Alcalde Bagüés
    • 1
    Email author
  • Wendelin Feiten
    • 1
  • Tim Tiedemann
    • 2
  • Christian Backe
    • 2
  • Dhiraj Gulati
    • 3
  • Steffen Lorenz
    • 4
  • Peter Conradi
    • 5
  1. 1.Siemens AG Corporate TechnologyMunichGermany
  2. 2.DFKI GmbHRobotics Innovation CenterBremenGermany
  3. 3.fortiss GmbHMunichGermany
  4. 4.NXP Semiconductors Germany GmbHHamburgGermany
  5. 5.ALL4IP TECHNOLOGIES GmbH & Co. KGDarmstadtGermany

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