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arXiv · 2208.03525

Stochastic MPC with Dual Control for Autonomous Driving with Multi-Modal Interaction-Aware Predictions

Siddharth H. Nair·Vijay Govindarajan·Theresa Lin·Yan Wang·Eric H. Tseng·Francesco Borrelli
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Abstract

We propose a Stochastic MPC (SMPC) approach for autonomous driving which incorporates multi-modal, interaction-aware predictions of surrounding vehicles. For each mode, vehicle motion predictions are obtained by a control model described using a basis of fixed features with unknown weights. The proposed SMPC formulation finds optimal controls which serves two purposes: 1) reducing conservatism of the SMPC by optimizing over parameterized control laws and 2) prediction and estimation of feature weights used in interaction-aware modeling using Kalman filtering. The proposed approach is demonstrated on a longitudinal control example, with uncertainties in predictions of the autonomous and surrounding vehicles.

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Siddharth H. Nair, Vijay Govindarajan, Theresa Lin, Yan Wang, Eric H. Tseng, Francesco Borrelli. 2022-08-06. Stochastic MPC with Dual Control for Autonomous Driving with Multi-Modal Interaction-Aware Predictions. https://arxiv.org/abs/2208.03525

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