基于遗传算法的自动驾驶汽车过减速带自适应速度控制方法研究

IF 1 4区 工程技术 Q4 ENGINEERING, MECHANICAL
Longjun Wang, Zhiyong Yang, Xiangdong Chen, R. Zhang, Yu Zhou
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引用次数: 1

摘要

摘要当自动驾驶汽车通过不平坦的道路,特别是高速公路上连续的速度控制凸起时,其速度将对驾驶的安全性和舒适性产生重大影响。如何自动选择最合适的速度已成为实践研究的课题。本文研究了自动驾驶汽车在高速公路上通过SCH时悬架系统的非线性振动过程。本文首先建立了四自由度(4-DOF)非线性半车辆模型和梯形SCH的仿真函数,然后使用Runge–Kutta方法对悬架系统的运动微分方程进行了数值求解。在下一部分中,本文选择遗传算法建立多目标优化问题模型,以车身的垂直位移、悬架的动态挠度和轮胎的动态载荷为优化目标,并结合统一目标函数的方法来寻找最优通过速度。最后,设计并实现了车辆在传统被动悬架、半主动悬架、主动悬架三种情况下的多目标优化问题的求解过程,并将优化状态与预优化状态进行了比较,验证了优化模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on adaptive speed control method of an autonomous vehicle passing a speed bump on the highway based on a genetic algorithm
Abstract. When autonomous vehicles pass through uneven roads, especially the consecutive speed control humps (SCHs) on expressways, the speed of them will have a significant influence on the safety and comfort of driving. How to automatically select the most appropriate speed has become a practical research subject. This paper studies the nonlinear vibration process of the suspension system when the autonomous vehicle passes through the SCHs on a highway. Firstly, the paper establishes a four-degree-of-freedom (4-DOF) nonlinear half-vehicle model and a stimulation function of trapezoidal SCHs and then uses the Runge–Kutta method to numerically solve the differential equations of motion of the suspension system. In the next part, the paper chooses the genetic algorithm to build a multi-objective optimization problem model, which selects the vertical displacement of the vehicle body, the suspension's dynamic deflection and the dynamic load of the tire as optimization objectives and combines the method of the unified objective function to find the optimal passing speed. Finally, the paper designs and carries out the solution process of the multi-objective optimization problem for the vehicle under three scenarios, conventional passive suspension, semi-active suspension, active suspension, and compares the optimized state with the pre-optimized state to prove the effectiveness of the optimization model.
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来源期刊
Mechanical Sciences
Mechanical Sciences ENGINEERING, MECHANICAL-
CiteScore
2.20
自引率
7.10%
发文量
74
审稿时长
29 weeks
期刊介绍: The journal Mechanical Sciences (MS) is an international forum for the dissemination of original contributions in the field of theoretical and applied mechanics. Its main ambition is to provide a platform for young researchers to build up a portfolio of high-quality peer-reviewed journal articles. To this end we employ an open-access publication model with moderate page charges, aiming for fast publication and great citation opportunities. A large board of reputable editors makes this possible. The journal will also publish special issues dealing with the current state of the art and future research directions in mechanical sciences. While in-depth research articles are preferred, review articles and short communications will also be considered. We intend and believe to provide a means of publication which complements established journals in the field.
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