In this paper, an explicit decision tree approach for automated driving is proposed. The ego vehicle operates in traffic that is modeled as a discrete-time Markov chain, the state of which is only partially observable. In this setting, the automated driving policy is generated from a decision tree algorithm offline operation to create an explicit implementation for the online use. Simulation results of an implementation of this approach for automated driving on a two-lane highway are reported to illustrate the potential of this approach.
- Dynamic Systems and Control Division
An Explicit Decision Tree Approach for Automated Driving
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Li, N, Chen, H, Kolmanovsky, I, & Girard, A. "An Explicit Decision Tree Approach for Automated Driving." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T45A003. ASME. https://doi.org/10.1115/DSCC2017-5099
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