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• W3170300491 abstract "We propose an integrated prediction and planning system for autonomous driving which uses rational inverse planning to recognise the goals of other vehicles. Goal recognition informs a Monte Carlo Tree Search (MCTS) algorithm to plan optimal maneuvers for the ego vehicle. Inverse planning and MCTS utilise a shared set of defined maneuvers and macro actions to construct plans which are explainable by means of rationality principles. Evaluation in simulations of urban driving scenarios demonstrate the system&#x2019;s ability to robustly recognise the goals of other vehicles, enabling our vehicle to exploit non-trivial opportunities to significantly reduce driving times. In each scenario, we extract intuitive explanations for the predictions which justify the system&#x2019;s decisions." @default.
• W3170300491 created "2021-06-22" @default.
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• W3170300491 date "2021-05-30" @default.
• W3170300491 modified "2023-10-01" @default.
• W3170300491 title "Interpretable Goal-based Prediction and Planning for Autonomous Driving" @default.
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• W3170300491 doi "https://doi.org/10.1109/icra48506.2021.9560849" @default.
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