The content introduces an innovative approach to automated lane merging using game theory and predictive control. It discusses the challenges in traditional methods, learning-based approaches, and the proposed integrated planner's effectiveness in handling interactions in dense traffic scenarios.
The authors model the lane-merging problem as a gap selection process inspired by human drivers. They introduce a matrix game to handle multi-modal driving behavior and utilize BMPC to account for uncertain behavior modes of surrounding vehicles. The proposed planner is validated using real traffic data, demonstrating its efficiency.
Key points include the formulation of trajectory selection as a matrix game, the introduction of BMPC to address uncertain behavior modes, and the validation of the integrated planner with real traffic data.
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by Luyao Zhang,... a las arxiv.org 03-11-2024
https://arxiv.org/pdf/2311.14916.pdfConsultas más profundas