一种适用于极端驾驶条件的汽车伸缩平台设计

Chengyuan Gao, Zhuolun Li, Yuntian Zhao, Zheng Zhu, Zhenzhong Jia
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引用次数: 0

摘要

该模型对于评估极端条件下车辆控制的自动驾驶算法具有指导意义。有了定制的结构,按比例缩放的汽车可以帮助评估车辆与外部环境之间的相互作用,而这些相互作用很难以合理的成本模拟出来。然而,目前市场上还没有一款规模化汽车能够实现四轮独立转矩控制和独立转向控制。在本文中,我们设计并构建了一个能够实现这些功能的缩放汽车平台。我们还通过初步实验证明了它的流动性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Scaled-car Platform for Extreme Driving Conditions
The scaled-car is instructive for evaluating autonomous driving algorithms for vehicle control under extreme conditions. With customized structures, scaled-cars can help evaluate the interactions between vehicle and external environment that are hard to simulate at an affordable cost. However, there is no scaled-car on the market that can achieve four-wheel independent torque control and independent steering control. In this paper, we design and build a scaled-car platform that is capable of these functionalities. We also demonstrate its mobility through preliminary experiments.
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