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Sensors for Automated Driving

In: Autonomous Vehicles

Author

Listed:
  • Stefan Muckenhuber

    (Scientist, University of Graz
    Senior Researcher, Virtual Vehicle Research Center)

  • Kenan Softic

    (VIRTUAL VEHICLE Research GmbH)

  • Anton Fuchs

    (Virtual Vehicle Research Center
    Adjunct Professor, Graz University of Technology)

  • Georg Stettinger

    (VIRTUAL VEHICLE Research GmbH)

  • Daniel Watzenig

    (VIRTUAL VEHICLE Research GmbH)

Abstract

A sensor system capable of supporting automated driving functions needs to provide both reliable localization of the vehicle and robust environment perception of the vehicle’s surrounding. The following chapter introduces the working principles and the state of the art of automotive sensors for localization (GNSS and INS) and environment perception (camera, radar and LIDAR), correspondingLight Detection And Ranging (LIDAR) sensormodelsSensor modeland sensor fusionSensor fusion techniques. Sensor models will allow for the replacement of conventional test drives and physical component tests by using simulations in virtual test environments to meet the increasing requirements of automated vehicles with respect to development costs, time and safety. Considering the multitude and complexity of possible environmental conditions, realistic simulation of perception sensors is a particularly demanding topic. To increase the performance of a sensor system, compensate for limitations of each sensor modality, and increase the overall robustness of the system, sensor fusion techniques are an important subject in automotive research.

Suggested Citation

  • Stefan Muckenhuber & Kenan Softic & Anton Fuchs & Georg Stettinger & Daniel Watzenig, 2021. "Sensors for Automated Driving," Perspectives in Law, Business and Innovation, in: Steven Van Uytsel & Danilo Vasconcellos Vargas (ed.), Autonomous Vehicles, edition 1, pages 115-146, Springer.
    • Handle: RePEc:spr:perchp:978-981-15-9255-3_6
    DOI: 10.1007/978-981-15-9255-3_6
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