NDLI: Towards speed-independent road-type classification

Content Provider	IEEE Xplore Digital Library
Author	Shifeng Wang Kodagoda, S. Khushaba, R.
Copyright Year	2012
Description	Author affiliation: Centre for Autonomous Systems (CAS), Faculty of Engineering and IT, University of Technology, Sydney (UTS), Sydney, Australia (Shifeng Wang; Kodagoda, S.; Khushaba, R.)
Abstract	The knowledge of terrain types is not only useful for improving passenger's safety and comfort, but also for bounding safe navigation routes for autonomous vehicles. Most of the work in the literature is limited to rover operations at slower speeds or rovers with rigid wheels. This paper discusses and presents a critical analysis of speed independency of classifiers for passenger vehicles with tyres at road operating speeds. The suitability of using different features calculated based on vertically mounted accelerometer data as well as road profile data were analyzed. The experimental results agree with the literature, where speed independency could be achieved by using the Fast Fourier Transform (FFT) features extracted from the estimated road profiles. However, we also show that it is possible to achieve comparable results by extracting different features directly from acceleration data. This eliminates the requirement of accurate knowledge of the vehicle model parameters or speed of the vehicle.
Starting Page	614
Ending Page	619
File Size	194086
Page Count	6
File Format	PDF
ISBN	9781467318716
e-ISBN	9781467318723
e-ISBN	9781467318709
DOI	10.1109/ICARCV.2012.6485228
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Roads Vehicles Feature extraction Acceleration Accelerometers Sensors Asphalt autonomous vehicle road type classification acceleration road profile
Content Type	Text
Resource Type	Article

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