Pedestrian-aware Model Predictive Controller for Design of Considerate Autonomous Driving

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  • モデル予測制御による歩行者への配慮を意識した自動運転の設計

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<p>Driving in roads shared with pedestrians remains to be a challenging research problem in suburban/urban autonomous driving scenario. Interacting with pedestrians and making considerate decisions require high level decision making which is close to that of humans. This paper attempts to propose a multi-mode pedestrian model and a model predictive control (MPC) framework that uses the pedestrian model to predict the interactive behavior of the pedestrian. A probability weighted ARX (PrARX) model is used as the pedestrian model. This model can represent both decision making and motion of the pedestrian considering the interaction with ego car. The allowed risk levels of the controller is tunable to create a more personal driving behavior. The decision entropy of the pedestrian is also included as a cost factor in the MPC. This makes the pedestrian's decision making process easier and leads to realization of considerate driving. The validation of proposed model is performed based on the vehicle-crowd interaction (VCI) - CITR dataset and the performance of the controller is demonstrated in simulations using MATLAB.</p>

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