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Challenges and Opportunities of Artificial Intelligence for Automated Driving

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Advanced Microsystems for Automotive Applications 2018 (AMAA 2018)

Part of the book series: Lecture Notes in Mobility ((LNMOB))

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Abstract

The advancement of automated driving (AD) depends on a multitude of influencing factors, however, achieving higher levels of automation fundamentally hinges on the capabilities of Artificial Intelligence (AI) to perform driving tasks. Improvements in AI hardware and the availability of large amounts of data (Big Data) have fueled the rapid increase in AD-related research and development activities over the past decade and are thus also the key indicators for future development. The shift from humans to AI in vehicle control unlocks many of the well-established potentials of AD, but is also the root for many non-technical issues that affect its introduction. Starting from the state of the art of AI for AD this chapter discusses key challenges and opportunities that mark the development path.

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Notes

  1. 1.

    Available online at www.connectedautomateddriving.eu.

  2. 2.

    A coordinated plan has been announced for the end of 2018.

  3. 3.

    1.5 billion as part of the Horizon 2020 programme, 2.5 billion from public-private partnerships and over 0.5 billion via the European Fund for Strategic Investment.

References

  1. McCarthy, J.: Computer Controlled Cars, Essay (1969)

    Google Scholar 

  2. Touretzky, D., Pomerlau, D.: What’s hidden in the hidden layers? BYTE 14, 227–233 (1989)

    Google Scholar 

  3. Raina, R., Madhavan, A., Ng, A.: Large-scale deep unsupervised learning using graphics processors. In: Proceedings of the 26th Annual Conference on Machine Learning, ICML 2009, pp. 873–880 (2009)

    Google Scholar 

  4. Turing, A.M.: Computing machinery and intelligence. Mind 49, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  5. Döbel, I., Leis, M., Vogelsang, M.M., et al.: Machine Learning - Competencies, Applications and Research Needs. Frauenhofer Society (2018). (in German)

    Google Scholar 

  6. Dally, W.: High-performance hardware for machine learning. NIPS Tutorial (2015)

    Google Scholar 

  7. Göhring, D., Latotzky, D., Wang, M., Rojas, R.: Semi-autonomous car control using brain computer interfaces. Advances in Intelligent Systems and Computing, vol. 94, pp. 393–408 (2013)

    Google Scholar 

  8. Shalev-Shwartz, S., Shammah, S., Shashua, A.: On a formal model of safe and scalable self-driving cars (2018). arXiv:1708.06374v5

  9. Slusallek, P.: Understanding the world with AI: training & validating autonomous vehicles with synthetic data. Talk Presented at Interactive Symposium on Research and Innovation for CAD in Europe at Tech Gate, Vienna, 20 April 2018

    Google Scholar 

  10. Probst, L., Pedersen, B., Lefebvre, V., Dakkak-Arnoux, L.: USA-China-EU plans for AI: where do we stand? Digital Transformation Monitor of the European Commission (2018)

    Google Scholar 

  11. Ding, J.: Deciphering China’s AI Dream, Governance of AI Program. University of Oxford (2018)

    Google Scholar 

  12. Churchill, O.: Chinas AI dreams. Nature 553, S10–S12 (2018). https://doi.org/10.1038/d41586-018-00539-y

    Article  Google Scholar 

  13. KI Bundesverband e.V.: Artificial Intelligence: State of the Art and Catalogue of Measures (2018). (in German)

    Google Scholar 

  14. Kalra, N., Paddock, S.M.: Driving to safety: how many miles of driving would it take to demonstrate autonomous vehicle reliability? RAND Corporation, Santa Monica (2016). https://www.rand.org/pubs/research_reports/RR1478.html

  15. Schuman, C.D., et al.: A survey of neuromorphic computing and neural networks in hardware (2017). arXiv:1705.06963v1

  16. Esser, S.K., et al.: Convolutional networks for fast, energy-efficient neuromorphic computing. PNAS 113(41), 11441–11446 (2016)

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful for fruitful cooperation with the contractual partners of the Coordination and Support Actions “Safe and Connected Automation of Road Transport” (SCOUT) and “Coordination of Automated Road Transport Deployment for Europe” (CARTRE). The SCOUT and CARTRE projects have received funding from the EU’s Horizon 2020 programme under grant agreements No. 713843 and 724086, respectively. The section on AI hardware further draws from investigations carried out as part of the SCORE project, which has also received funding under the EU’s Horizon 2020 programme.

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Correspondence to Benjamin Wilsch .

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Wilsch, B., Elrofai, H., Krune, E. (2019). Challenges and Opportunities of Artificial Intelligence for Automated Driving. In: Dubbert, J., Müller, B., Meyer, G. (eds) Advanced Microsystems for Automotive Applications 2018. AMAA 2018. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-319-99762-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-99762-9_11

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  • Publisher Name: Springer, Cham

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