Longitudinal vehicle guidance using neural networks
Longitudinal vehicle guidance using neural networks
复制标题
使用神经网络的纵向车辆引导
DOI：
10.1109/cira.2005.1554356
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
C. Wurmthaler
中科院分区：
文献类型：
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作者：
A. Tahirovic;S. Konjicija;Z. Avdagić;G. Meier;C. Wurmthaler
本文的目的是显示一个简单的能力，使用神经网络在纵向车辆制导。主要动机是神经网络有机会从获得的真实的驾驶员数据中学习，并再现从非常舒适到非常运动的许多驾驶员行为风格。这种可能性与模拟模型为基础的纵向轨迹生成。该模型针对不同类型的驾驶员行为使用了可调节的舒适性参数。实验结果，获得与奥迪试验车，也提出了。
The purpose of this paper is to show a simple ability of using neural networks in longitudinal vehicle guidance. The main motivation is an opportunity of neural networks to learn from acquired real driver data, as well as to reproduce many driver behaviour styles raging from extremely comfort to extremely sportive ones. This possibility is shown with a simulated model based longitudinal trajectory generation. This model has used an adjustable comfort parameter for different sorts of driver behaviour. Experiment results, obtained with Audi test vehicle, are also presented.