Abstract
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.
Highlights
Autonomous ground vehicles recognize the surrounding environment and autonomously generate driving commands
This method may work as a redundant sensor in the localization process when in conjunction with a Global Positioning System (GPS) or be a backup sensor when GPS is unavailable, which both increase the reliability of the navigation system
This paper presented a non-dead-reckoning-based localization method using an inertial measurement units (IMUs) sensor without the concern of error accumulation
Summary
Autonomous ground vehicles recognize the surrounding environment and autonomously generate driving commands. The basic concept for our approach is comparing the profile of the current position with a pre-indexed road profile database, which does not require the addition of a GPS signal This method may work as a redundant sensor in the localization process when in conjunction with a GPS or be a backup sensor when GPS is unavailable, which both increase the reliability of the navigation system. A spectrogram is a two-dimensional plot in the time-frequency domain, so the characteristics of signals are displayed with richer information Another benefit of a candomain, use image processing techniques forare feature matching because the spectrogram is displayed in a so the characteristics of signals displayed with richer information. Another benefit of a spectrogram is the easy rejection of measurement noise.
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