TR2023-084
Decision Making for Automated Driving by Reachability of Parameterized Maneuvers
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- "Decision Making for Automated Driving by Reachability of Parameterized Maneuvers", World Congress of the International Federation of Automatic Control (IFAC), Ishii, H. and Ebihara, Y. and Imura, J. and Yamakita, M., Eds., DOI: 10.1016/j.ifacol.2023.10.018, July 2023, pp. 7852-7857.BibTeX TR2023-084 PDF
- @inproceedings{DiCairano2023jul,
- author = {Di Cairano, Stefano and Skibik, Terrence and Vinod, Abraham P. and Weiss, Avishai and Berntorp, Karl},
- title = {Decision Making for Automated Driving by Reachability of Parameterized Maneuvers},
- booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
- year = 2023,
- editor = {Ishii, H. and Ebihara, Y. and Imura, J. and Yamakita, M.},
- pages = {7852--7857},
- month = jul,
- publisher = {Elsevier},
- doi = {10.1016/j.ifacol.2023.10.018},
- url = {https://www.merl.com/publications/TR2023-084}
- }
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- "Decision Making for Automated Driving by Reachability of Parameterized Maneuvers", World Congress of the International Federation of Automatic Control (IFAC), Ishii, H. and Ebihara, Y. and Imura, J. and Yamakita, M., Eds., DOI: 10.1016/j.ifacol.2023.10.018, July 2023, pp. 7852-7857.
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MERL Contacts:
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Research Areas:
Abstract:
We consider a decision making system for automated driving that has the objective of determining what maneuvers are feasible for the current vehicle, route, and traffic conditions. For the maneuvers determined to be feasible, a motion planner can then generate the trajectories that achieve the corresponding goals, without the risk of wasting computations in searching for a trajectory of an impossible maneuver. We solve the decision making problem by constructing backward reachable sets for goals and collision areas, based on maneuvers that are generated by dynamical models with decision parameters. Online, we only need to check the existence of parameter values that provide membership of the state-parameter vector in a goal reachable set, and non-membership in all collision reachable sets, which entails simple and fast computations. We evaluate the method in scenarios involving lane change and braking maneuvers.
Related News & Events
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NEWS MERL presents 9 papers at 2023 IFAC World Congress Date: July 9, 2023 - July 14, 2023
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Diego Romeres; Abraham P. Vinod
Research Areas: Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researchers presented 9 papers and organized 2 invited/workshop sessions at the 2023 IFAC World Congress held in Yokohama, JP.
MERL's contributions covered topics including decision-making for autonomous vehicles, statistical and learning-based estimation for GNSS and energy systems, impedance control for delta robots, learning for system identification of rigid body dynamics and time-varying systems, and meta-learning for deep state-space modeling using data from similar systems. The invited session (MERL co-organizer: Ankush Chakrabarty) was on the topic of “Estimation and observer design: theory and applications” and the workshop (MERL co-organizer: Karl Berntorp) was on “Gaussian Process Learning for Systems and Control”.
- MERL researchers presented 9 papers and organized 2 invited/workshop sessions at the 2023 IFAC World Congress held in Yokohama, JP.