Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

Muzammel, M. and Yusoff, M.Z. and Malik, A.S. and Saad, M.N.M. and Meriaudeau, F. (2017) Motorcyclists safety system to avoid rear end collisions based on acoustic signatures. Proceedings of SPIE - The International Society for Optical Engineering, 10338.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87. We believe that this method can help to reduce a significant number of motorcycle accidents.

Item Type: Article
Impact Factor: cited By 0
Departments / MOR / COE: Centre of Excellence > Center for Intelligent Signal and Imaging Research
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 23 Apr 2018 01:02
Last Modified: 23 Apr 2018 01:02
URI: http://scholars.utp.edu.my/id/eprint/20294

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