Thanks to visit codestin.com
Credit goes to link.springer.com

Skip to main content

Automated Driving

Computers take the wheel

  • Chapter
Digital Transformation
  • 6228 Accesses

  • 3 Citations

Summary

Digital networking and autonomous driving functions mark a new and fascinating chapter in the success history of automobile manufacture, which stretches back well over a century already. With powerful environment recognition, highly accurate localization and low-latency communication technology, vehicle and traffic safety will thus increase dramatically. Precise, fully automated vehicle positioning of autonomously driven electric cars creates the conditions for introducing innovative high-current charging technologies located underground. If autonomous or highly automated vehicles share information with intelligent traffic controls in future, then this may lead to a significantly more efficient utilization of existing traffic infrastructures and marked reductions in traffic-related pollutant emissions. These are three examples that underscore the enormous significance of electric mobility together with autonomous driving functions for the development of a truly sustainable mobility. In this process, the range of scientific-technical challenges in need of a solution is extraordinarily broad. Numerous Fraunhofer institutes are involved in this key development process for our national economy, contributing not merely expert competencies at the highest scientific-technical level, but also practical experience in the industrial implementation of high technologies. In what follows, we take a look at some of the current topics of research. These include autonomous driving functions in complex traffic situations, cooperative driving maneuvers in vehicle swarms, low-latency communication, digital maps and precise localization. Also, security of functions and security against manipulation for driverless vehicles, digital networking and data sovereignty in intelligent traffic systems is considered. Finally, range extension and fast-charging capabilities for autonomous electric vehicles through to new vehicle design, modular vehicle construction and scalable functionality is addressed. And even though the automobile sector is the focus of our attention here, it is worth taking a look at interesting Fraunhofer developments in autonomous logistics transport systems, driverless mobile machines in agricultural engineering, autonomous rail vehicle technology, and unmanned ships and underwater vehicles.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+
from £29.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 103.50
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
GBP 129.99
Price includes VAT (United Kingdom)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Sources and literature

  1. IHS Automotive (2014): Emerging technologies. Autonomous cars – Not if, but when

    Google Scholar 

  2. Victoria Transport Institute (2013): Autonomous vehicle implementation predictions. Implications for transport planning. http://orfe.princeton.edu/~alaink/SmartDrivingCars/Reports&Speaches_External/Litman_AutonomousVehicleImplementationPredictions.pdf [letzter Zugriff: 03.07.2017]

  3. Strategy& (2014): Connected Car Studie 2014

    Google Scholar 

  4. O. Wyman Consulting (2012): Car-IT Trends, Chancen und Herausforderungen für IT- Zulieferer

    Google Scholar 

  5. Zentrum für europäische Wirtschaftsforschung ZEW, Niedersächsisches Institut für Wirtschaftsforschung (NIW) (2009): Die Bedeutung der Automobilindustrie für die deutsche Volkswirtschaft im europäischen Kontext. Endbericht an das BMWi

    Google Scholar 

  6. McKinsey (2014): Connected car, automotive value chain unbound. Consumer survey

    Google Scholar 

  7. Appinions (2014): Autonomous cars. An industry influence study

    Google Scholar 

  8. J.R. Ziehn (2012): Energy-based collision avoidance for autonomous vehicles. Masterarbeit, Leibniz Universität Hannover

    Google Scholar 

  9. M. Ruf, J.R. Ziehn, B. Rosenhahn, J. Beyerer, D. Willersinn, H. Gotzig (2014): Situation Prediction and Reaction Control (SPARC). In: B. Färber (Hrsg.): 9. Workshop Fahrerassistenzsysteme (FAS), Darmstadt, Uni-DAS e.V., S. 55-66

    Google Scholar 

  10. J. Ziegler, P. Bender, T. Dang, and C. Stiller (2014): Trajectory planning for Bertha. A local, continuous method. In: Proceedings of the 2014 IEEE Intelligent Vehicles Symposium (IV), S. 450-457

    Google Scholar 

  11. J.R. Ziehn, M. Ruf, B. Rosenhahn, D. Willersinn, J. Beyerer, H. Gotzig (2015): Correspondence between variational methods and hidden Markov models. In: Proceedings of the IEEE Intelligent Vehicles Symposium (IV), S. 380-385

    Google Scholar 

  12. M. Ruf, J.R. Ziehn, D. Willersinn, B. Rosenhahn, J. Beyerer, H. Gotzig (2015): Global trajectory optimization on multilane roads. In: Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems (ITSC), S. 1908-1914

    Google Scholar 

  13. J.R. Ziehn, M. Ruf, D. Willersinn, B. Rosenhahn, J. Beyerer, H. Gotzig (2016): A tractable interaction model for trajectory planning in automated driving. In: Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), S. 1410-1417

    Google Scholar 

  14. N. Evestedt, E. Ward, J. Folkesson, D. Axehill (2016): Interaction aware trajectory planning for merge scenarios in congested traffic situations. In: Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), S. 465-472

    Google Scholar 

  15. T. Emter und J. Petereit (2014): Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots. In: Proc. SPIE 9121: Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications

    Google Scholar 

  16. T. Emter, A. SaltoÄŸlu, J. Petereit (2010): Multi-sensor fusion for localization of a mobile robot in outdoor environments. In: ISR/ROBOTIK 2010, Berlin, VDE Verlag, S. 662-667

    Google Scholar 

  17. C. Frese, A. Fetzner, C. Frey (2014): Multi-sensor obstacle tracking for safe human-robot interaction. In: ISR/ROBOTIK 2010, Berlin, VDE Verlag, S. 784-791

    Google Scholar 

  18. C. Herrmann, T. Müller, D. Willersinn, J. Beyerer (2016): Real-time person detection in low-resolution thermal infrared imagery with MSER and CNNs. In: Proc. SPIE 9987, Electro-Optical and Infrared Systems: Technology and Applications

    Google Scholar 

  19. J. Uhrig, M. Cordts, U. Franke, T. Brox (2016): Pixel-level encoding and depth layering for instance-level semantic segmentation. 38th German Conference on Pattern Recognition (GCPR), Hannover, 12.-15. September

    Google Scholar 

  20. C. Frese und J. Beyerer (2011): Kollisionsvermeidung durch kooperative Fahrmanöver. In: Automobiltechnische Zeitschrift ATZ Elektronik, Jg. 6, Nr. 5, S. 70-75

    Article  Google Scholar 

  21. C. Frese (2012): Planung kooperativer Fahrmanöver für kognitive Automobile. Dissertation, Karlsruher Schriften zur Anthropomatik, Bd. 10, KIT Scientific Publishing

    Google Scholar 

  22. M. Düring, K. Lemmer (2016): Cooperative maneuver planning for cooperative driving. In: IEEE Intelligent Transportation Systems Magazine, Bd. 8, Nr. 3, S. 8-22

    Article  Google Scholar 

  23. J. Boudaden, F. Wenninger, A. Klumpp, I. Eisele, C. Kutter (2017): Smart HVAC sensors for smart energy. International Conference and Exhibition on Integration Issues of Miniaturized Systems (SSI), Cork, 8.-9. März

    Google Scholar 

  24. https://www.fraunhofer.de/en/research/lighthouse-projects-fraunhofer-initiatives/industrial-data-space.html [letzter Zugriff: 03.07.2017]

  25. http://www.edda-bus.de/ [letzter Zugriff: 03.07.2017]

  26. F.-P. Schiefelbein, F. Ansorge (2016): Innovative Systemintegration für elektrische Steckverbinder und Anschlusstechnologien. In: Tagungsband GMM-Fb. 84: Elektronische Baugruppen und Leiterplatten (EBL), Berlin, VDE Verlag; F. Ansorge (2016): Steigerung der Systemzuverlässigkeit durch intelligente Schnittstellen und Steckverbinder im Bordnetz. Fachtagung Effizienzsteigerung in der Bordnetzfertigung durch Automatisierung, schlanke Organisation und Industrie-4.0-Ansätze, Nürnberg, 5. Oktober

    Google Scholar 

  27. G. Brux (2005): Projekt RUBIN. Automatisierung der Nürnberger U-Bahn. Der Eisenbahningenieur, Nr. 11, S. 52-56

    Google Scholar 

  28. http://www.ingenieur.de/Branchen/Verkehr-Logistik-Transport/Fahrerlos-Paris-Die-Metro-14-um-sechs-Kilometer-verlaengert [letzter Zugriff: 03.07.2017]

  29. A. Schwarte, M. Arpaci (2013): Refurbishment of metro and commuter railways with CBTC to realize driverless systems. In: Signal und Draht, Jg. 105, Nr. 7/8, S. 42-47

    Google Scholar 

  30. Verband der Automobilindustrie e.V. (2015): Automatisierung Von Fahrerassistenzsystemen zum automatisierten Fahren; Institute for Mobility Research (2016): Autonomous Driving The Impact of Vehicle Automation on Mobility Behaviour

    Google Scholar 

  31. http://www.unmanned-ship.org/munin/ [letzter Zugriff: 03.07.2017]

  32. https://www.fraunhofer.de/content/dam/zv/de/presse-medien/Pressemappen/hmi2016/Presseinformation%20Autonome%20Systeme.pdf [letzter Zugriff: 03.07.2017]

  33. https://arggonauts.de/de/technologie/ [letzter Zugriff: 03.07.2017]

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer-Verlag GmbH Germany, part of Springer Nature

About this chapter

Cite this chapter

Clausen, U., Klingner, M. (2019). Automated Driving. In: Neugebauer, R. (eds) Digital Transformation. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58134-6_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-58134-6_22

  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-58133-9

  • Online ISBN: 978-3-662-58134-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics