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首页> 外文期刊>Artificial life and robotics >Merging trajectory generation method using real-time optimization with enhanced robustness against sensor noise
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Merging trajectory generation method using real-time optimization with enhanced robustness against sensor noise

机译：使用实时优化的合并轨迹生成方法，具有增强的抗传感器噪声鲁棒性

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摘要

To reduce drivers' mental load and traffic congestion caused by merging maneuver, a merging trajectory generation method aiming for practical automatic driving was proposed in the past research by the authors. In this paper, the robustness of the method against sensor noises is enhanced. The robustness is improved by the dummy optimization variables that relax the equality constraints and the barrier functions. The stage costs composed by these introduced dummy variables are designed to generate safe and smooth merging maneuver. The effectiveness of the proposed method for a typical case is observed in the simulation results. To check if the proposed method works well under different initial conditions, 116 initial conditions are generated randomly. The proposed method solves all the cases of merging problem, while the conventional method fails in 80% of the cases.
机译：为了减少驾驶员因合并而引起的精神负担和交通拥堵，作者在过去的研究中提出了一种针对实际自动驾驶的合并轨迹生成方法。在本文中，该方法针对传感器噪声的鲁棒性得到了增强。通过放宽等式约束和势垒函数的虚拟优化变量可以提高鲁棒性。由这些引入的虚拟变量组成的阶段成本旨在生成安全且平滑的合并策略。仿真结果表明了该方法在典型情况下的有效性。为了检查所提出的方法在不同的初始条件下是否工作良好，随机生成了116个初始条件。提出的方法解决了所有合并问题，而传统方法在80％的情况下均失败。

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