Road Safety Features Identification Using the Inertial Measurement Unit
| Autor: | Franc Dimc, Gianmarco Baldini, Raimondo Giuliani |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Dynamic time warping
Computer science 010401 analytical chemistry Feature extraction 020206 networking & telecommunications 02 engineering and technology Accelerometer computer.software_genre 01 natural sciences 0104 chemical sciences Units of measurement Identification (information) Inertial measurement unit Feature (computer vision) Road surface 0202 electrical engineering electronic engineering information engineering Data mining Electrical and Electronic Engineering Instrumentation computer |
| Zdroj: | IEEE Sensors Letters. 2:1-4 |
| ISSN: | 2475-1472 |
| DOI: | 10.1109/lsens.2018.2880118 |
| Popis: | Recent studies have investigated the use of inertial measurement units to detect and report the presence of road irregularities on the surface and thus improve safety and maintenance of the transportation infrastructure. The results from the literature show that it is possible to detect the presence of various irregularities in the road surface and identify the type of irregularity with good accuracy using various statistical features. This article addresses specific irregularities called road safety features (RSF) and focuses on the identification of the RSF instances themselves rather than the RSF type identification, which leads to a more challenging problem. The authors have collected data from accelerometers and gyroscopes in an Inertial Motion Unit (IMU) from 42.5 kms of vehicle driving where RSF were present. In particular, two types of RSF were investigated: a rumble strip and a speed bumper. Two different approaches were used to classify the RSF: a feature-based approach derived from the research literature and a novel approach based on dynamic time warping (DTW). The results show that the approach based on Dynamic Time Warping (DTW) provides a very high level of identification accuracy. To the best of the authors' knowledge, this is the first attempt in the literature for the identification of specific road irregularities based on a large experimental dataset. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|