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Challenges for Automated Cooperative Driving: The AutoNet2030 Approach

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Automated Driving

Abstract

Automated driving is expected to significantly contribute to future safe and efficient mobility. Whereas classical automated approaches solely consider the host vehicle, AutoNet2030 aims to investigate a cooperative approach where communication is used to build decentralized control systems, facilitate cooperative traffic flow optimization, and enhance perception. This chapter introduces the concepts and methodology of AutoNet2030 in order to contribute to a cost-optimized and widely deployable automated driving technology.

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Notes

  1. 1.

    http://www.gcdc.net/i-game

  2. 2.

    http://www.adaptive-ip.eu

  3. 3.

    http://www.companion-project.eu

  4. 4.

    http://www.sae.org/misc/pdfs/automated_driving.pdf

References

  1. A. de La Fortelle, X. Qian, S. Diemer, J. Grégoire, F. Moutarde, S. Bonnabel. A. Marjovi, A. Martinoli, I. Llatser, A. Festag, K. Sjöberg, Network of Automated Vehicles: The AutoNet2030 Vision, in Proceedings of 21st World Congress on Intelligent Transport Systems, 2014

    Google Scholar 

  2. L. Xiao, F. Gao, Practical string stability of platoon of adaptive cruise control vehicles. IEEE Trans. Intell. Transp. Syst. 12(4), 1184–1194 (2011)

    Article  Google Scholar 

  3. S.Y. Han, Y.H. Chen, L. Wang, A. Abraham, Decentralized Longitudinal Tracking Control for Cooperative Adaptive Cruise Control Systems in a Platoon, in IEEE International Conference on Systems, Man, and Cybernetics, pp. 2013–2018, 2013

    Google Scholar 

  4. K.Y. Liang, Coordination and Routing for Fuel-Efficient Heavy-Duty Vehicle Platoon Formation, Licentiate Thesis, 2014

    Google Scholar 

  5. S. Gowal, R. Falconi, A. Martinoli, Local Graph-Based Distributed Control for Safe Highway Platooning, in IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 6070–6076, 2010

    Google Scholar 

  6. A. Marjovi, M. Vasic, J. Lemaitre, A. Martinoli, Distributed Graph-Based Convoy Control for Networked Intelligent Vehicles, in Proceedings of IEEE Intelligent Vehicles Symposium, pp. 138–143, 2015

    Google Scholar 

  7. K.M. Dresner, P. Stone, A multiagent approach to autonomous intersection management. J. Artif. Intell. Res. (JAIR) 31, 591–656 (2008)

    Article  Google Scholar 

  8. J. Gregoire, S. Bonnabel, A. de La Fortelle, Priority-Based Coordination of Robots, CoRR, vol. abs/1306.0, 2013

    Google Scholar 

  9. X. Qian, J. Gregoire, F. Moutarde, A. de La Fortelle, Priority-Based Coordination of Autonomous and Legacy Vehicles at Intersection, in Proceedings of the IEEE International. Conference on Intelligent Transportation Systems (ITSC), pp. 1166–1171, 2014

    Google Scholar 

  10. X. Qian, J. Gregoire, A. de La Fortelle, F. Moutarde, Decentralized Model Predictive Control for Smooth Coordination of Automated Vehicles at Intersection, in European Control Conference (ECC2015), 2015

    Google Scholar 

  11. N. Mattern, R. Schubert, A Hybrid Approach for ADAS Algorithm Development—From High-Level Prototypes to ECUs, in Proceedings of the 10th ITS European Congress, Helsinki, Finland

    Google Scholar 

  12. S. Kato, S. Tsugawa, K. Tokuda, T. Matsui, H. Fujii, Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications. IEEE Trans. Intell. Transp. Syst. 3(3), 155–161 (2002)

    Article  Google Scholar 

  13. H. Stubing, M. Bechler, D. Heussner, T. May, I. Radusch, H. Rechner, P. Vogel, simTD: A car-to-X system architecture for field operational tests. IEEE Commun. Mag. 48(5), 148–154 (2010)

    Article  Google Scholar 

  14. L. Hobert, A. Festag, I. Llatser, L. Altomare, F. Visintainer, A. Kovacs, Enhancements of V2X Communication in Support of Cooperative Autonomous Driving, to appear in IEEE Communications Magazine, 2015

    Google Scholar 

  15. M. Tsogas, N. Floudas, P. Lytrivis, A. Amditis, A. Polychronopoulos, Combined lane and road attributes extraction by fusing data from digital map, laser scanner and camera. Inf. Fusion 12(1), 28–36 (2011)

    Article  Google Scholar 

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Acknowledgement

The research work has been funded by the European FP7 project AutoNet2030 (Grant Agreement NO. 610542).

Author information

Authors and Affiliations

  1. Baselabs, Chemnitz, Germany

    Marcus Obst

  2. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Ali Marjovi, Milos Vasic, Iñaki Navarro & Alcherio Martinoli

  3. Institute of Communications and Computer Systems, Athens, Greece

    Angelos Amditis & Panagiotis Pantazopoulos

  4. Technische Universität Dresden, Dresden, Germany

    Ignacio Llatser

  5. Centre for Robotics, MINES ParisTech—PSL Research University, Paris, France

    Arnaud de La Fortelle & Xiangjun Qian

Authors
  1. Marcus Obst
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  2. Ali Marjovi
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  3. Milos Vasic
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  4. Iñaki Navarro
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  5. Alcherio Martinoli
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  6. Angelos Amditis
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  7. Panagiotis Pantazopoulos
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  8. Ignacio Llatser
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  9. Arnaud de La Fortelle
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  10. Xiangjun Qian
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Corresponding author

Correspondence to Marcus Obst .

Editor information

Editors and Affiliations

  1. Institute of Electrical Measurement and Measurement Signal Processing, Virtual Vehicle Research Center and Graz University of Technology, Graz, Austria

    Daniel Watzenig

  2. Institute of Automation and Control, Graz University of Technology, Graz, Austria

    Martin Horn

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Obst, M. et al. (2017). Challenges for Automated Cooperative Driving: The AutoNet2030 Approach. In: Watzenig, D., Horn, M. (eds) Automated Driving. Springer, Cham. https://doi.org/10.1007/978-3-319-31895-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-31895-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31893-6

  • Online ISBN: 978-3-319-31895-0

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