自动驾驶汽车导航的发展

S. Neusser, J. Nijhuis, L. Spaanenburg
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引用次数: 4

摘要

提出了一种利用神经网络模拟人类驾驶行为的自动驾驶汽车导航方法。结果是基于一个真正的人类司机在一辆真正的汽车中测量的动作。描述了汽车环境和驾驶过程中记录的信息。讨论了神经网络需要解决的问题。给出了驾驶任务的实际学习过程。对学习驾驶行为的质量进行了综述。实验表明,中型神经网络能够在5%的最大误差内近似驾驶行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developments in autonomous vehicle navigation
An approach to autonomous vehicle navigation using neural networks to imitate human driving behavior is presented. The results are based on the measured actions of a real human driver in a real car. The car environment and the information that is recorded during driving are described. The problem that should be solved by the neural network is discussed. The actual learning of the driving task is presented. The quality of the leaned driving behavior is reviewed. The experiments showed that medium-sized neural networks were able to approximate the driving behavior within a maximum error of 5%.<>
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