School of Mechanical Engineering, Pusan National University, Busan 46241, Korea.
Sensors (Basel). 2018 Oct 7;18(10):3344. doi: 10.3390/s18103344.
A road profile can be a good reference feature for vehicle localization when a Global Positioning System signal is unavailable. However, cost effective and compact devices measuring road profiles are not available for production vehicles. This paper presents a longitudinal road profile estimation method as a virtual sensor for vehicle localization without using bulky and expensive sensor systems. An inertial measurement unit installed in the vehicle provides filtered signals of the vehicle's responses to the longitudinal road profile. A disturbance observer was designed to extract the characteristic features of the road profile from the signals measured by the inertial measurement unit. Design synthesis based on a Kalman filter was used for the observer design. A nonlinear damper is explicitly considered to improve the estimation accuracy. Virtual measurement signals are introduced for observability. The suggested methodology estimates the road profile that is sufficiently accurate for localization. Based on the estimated longitudinal road profile, we generated spectrogram plots as the features for localization. The localization is realized by matching the spectrogram plot with pre-indexed plots. The localization using the estimated road profile shows a few meters accuracy, suggesting a possible road profile estimation method as an alternative sensor for vehicle localization.
当全球定位系统信号不可用时，道路轮廓可以作为车辆定位的一个很好的参考特征。然而，用于生产车辆的测量道路轮廓的经济型和紧凑型设备并不存在。本文提出了一种纵向道路轮廓估计方法，作为车辆定位的虚拟传感器，而无需使用庞大且昂贵的传感器系统。安装在车辆上的惯性测量单元提供了车辆对纵向道路轮廓响应的滤波信号。设计了一个干扰观测器，从惯性测量单元测量的信号中提取道路轮廓的特征。基于卡尔曼滤波器的设计综合用于观测器设计。明确考虑了非线性阻尼器以提高估计精度。引入了虚拟测量信号以提高可观测性。所提出的方法可以估计出足够精确的道路轮廓以用于定位。基于估计的纵向道路轮廓，我们生成了频谱图作为定位的特征。通过将频谱图与预索引的图谱进行匹配来实现定位。使用估计的道路轮廓进行定位可以达到几米的精度，这表明道路轮廓估计方法可以作为车辆定位的替代传感器。
