Optimal design of a driver assistance controller based on surrounding vehicle?s social behavior game model

Driver assistance control in the cut-in scenarios is challenging, since the controller needs to ensure driving safety and avoid unnecessary intervention, while considering the inter-action with surrounding vehicles. This paper proposes an optimal driver assistance con-troller considering the social behaviors of the surrounding vehicles to assist the drivers in the cut-in scenarios. To model the social behavior of the surrounding vehicle, we first for-mulate the interaction between the semi-autonomous vehicle and the surrounding vehicle as a misinformation game, which is achieved by assuming the surrounding vehicle is in-teracting with a hypothetical vehicle under the framework of non-cooperative game. Then, adaptive dynamic programming theory is utilized to find the Nash equilibrium, which is represented by deep neural networks and solved iteratively. Based on the established so-cial behavior model and the nonlinear driver-vehicle dynamic model, an affine input non-linear system model is obtained for the design of driver assistance controller, and the op-timal assistance control strategy is also derived under the structure of adaptive dynamic programming. Several numerical simulations and driver-in-the-loop simulator experiments are conducted for validation. Results show that the proposed strategy can assist the driver in the cut-in scenario while addressing different social interactions with the surround-ing vehicles. Importantly, by taking into account the surrounding vehicle's social behavior through our established social behavior model, our proposed strategy significantly outper-forms the no-interaction strategy both in terms of driving safety and intervention degree, validating its effectiveness and superiority.(c) 2022 Published by Elsevier Inc.