Abstract
Steering an autonomous vehicle requires the permanent adaptation of behavior in relation to the various situations the vehicle is in. This paper describes a research which implements such adaptation and optimization based on Reinforcement Learning (RL) which in detail purely learns from evaluative feedback in contrast to instructive feedback. Convergence of the learning process has been achieved at various experimental results revealing the impact of the different RL parameters. While using RL for autonomous steering is in itself already a novelty, additional attention has been given to new proposals for post-processing and interpreting the experimental data.
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References
Sutton, R., Barto, A.G.: Reinforcement Learning: An introduction. MIT-Press, Cambridge (2000)
Pommerleau, D.A.: Efficient Training of Artificial Neural Networks for Autonomous Navigation. Neural Computation 3 (1991)
Jochem, T.M., Pomerleau, D.A., Thorpe, C.E.: MANIAC: A Next Generation Neurally Based Autonomous Road Follower. In: Groen, F.C.A., Hirose, S., Thorpe, C.E. (eds.) IAS-3, Int. Conference on Intelligent autonomous Systems, Pittsburgh/PA, USA, February 15-18. IOS Press, Washington (1993)
Jochem, T.M., Pomerleau, D.A., Thorpe, C.E.: Vision Guided Lane Transition, Intelligent Vehicles 1995 Symposium, Detroit/MI, USA, September 25-26 (1995)
Baluja, S., Pomerleau, D.A.: Expectation-based selective attention for visual monitoring and control of a robot vehicle. Robotics and Autonomous System 22(3-4) (December 1997)
Franke, U., Gavrilla, D., Görzig, S., Lindner, F., Paetzold, F., Wöhler, C.: Autonomous Driving Goes Downtown. IEEE Intelligent Vehicles Systems 13(6), 40–48 (1998)
Dickmanns, E.D., Zapp, A.: Autonomous High Speed Road Vehicle Guidance by Computer Vision. In: Preprints of the 10th World Congress on Automatic Control, International Federation of Automatic Control, Munich, Germany, July 27-31, vol. 4 (1987)
Kuhnert, K.-D.: A Vision System for Real Time Road and Object Recognition for Vehicle Guidance. In: Proc. Mobile Robots, Cambridge, Massachusetts, Society of Photo-Optical Instrumentation Engineers, October 30-31. SPIE, vol. 727 (1986)
Dickmanns, E.D., Behringer, R., Dickmanns, D., Hildebrandt, T., Maurer, M., Thomanek, F., Schiehlen, J.: The Seeing Passenger Car VaMoRs-P. In: Intelligent Vehicles 1994 Symposium, Paris, France, October 24-26 (1994)
Krödel, M., Kuhnert, K.-D.: Pattern Matching as the Nucleus for either Autonomous Driving or Drive Assistance Systems. In: IEEE Intelligent Vehicle Symposium, Versailles, France, June 17-21 (2002)
Kuhnert, K.-D., Krödel, M.: Reinforcement Learning to drive a car by pattern matching. In: Van Gool, L. (ed.) DAGM 2002. LNCS, vol. 2449, p. 322. Springer, Heidelberg (2002)
Kuhnert, K.-D., Krödel, M.: Autonomous Driving by Pattern Matching and Reinforcement Learning. In: International Colloquium on Autonomous and Mobile Systems, Magdeburg, Germany, June 25-26 (2002)
Kuhnert, K.-D., Dong, W.: Über die lernende Regelung autonomer Fahrzeuge mit neuronalen Netzen, 18. Fachgespräch Autonome Mobile Systeme (AMS), December 4-5, Karlsruhe, Germany
Dong, W., Kuhnert, K.-D.: Robust adaptive control of honholonomic mobile robot with parameter and non-parameter uncertainties. IEEE Transaction on Robotics and Automation (2004)
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Kuhnert, KD., Krödel, M. (2005). Autonomous Vehicle Steering Based on Evaluative Feedback by Reinforcement Learning. In: Perner, P., Imiya, A. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2005. Lecture Notes in Computer Science(), vol 3587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11510888_40
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DOI: https://doi.org/10.1007/11510888_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26923-6
Online ISBN: 978-3-540-31891-0
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