Automated Vehicle Classification System for Austroads Standard Based Upon Laser Sensor Technology

Abstract

Traffic surveying systems using pneumatic road sensors are currently widely used in Australia for counting and classifying vehicles. However, these intrusive sensors disrupt traffic and expose technicians to significant road dangers. We propose a non-intrusive automated vehicle classification system for the AUSTROADS classification standard based upon laser sensor technology. The proposed system is capable of classifying vehicles in multi-lane, high-speed environments. Conventional Fourier-based denoising techniques are, however, unable to meet the design challenge due to a considerable amount of noise presented in measurement data that is induced by both the laser sensing device and high volume traffic in carriageways. This paper proposes an advanced wavelet-based denoising technique to greatly enhance the noise reduction performance of the proposed automated vehicle classification system.

Key Words:

• Automated vehicle classifi cation system
• laser sensor
• wavelet denoising

Additional information

Notes on contributors

W. Xiang

Dr Wei Xiang is a senior lecturer of electrical and electronic engineering in the Faculty of Engineering and Surveying at the University of Southern Queensland. His research areas of interest include wireless communications, signal processing, and coding and information theory. He received his PhD, MEng and BEng degrees in 2004, 2000 and 1997, respectively, from the University of South Australia and the University of Electronic Science and Technology of China.

C. Otto

Colin Otto is currently employed by the Queensland Department of Main Roads as an Intelligent Transport Systems (ITS) engineer. He currently works out of the Major Projects Office, to manage design and installation of ITS equipment on new construction projects for the rapidly expanding Translink Busway network. Colin completed a Bachelor of Electrical and Electronic Engineering from the University of Southern Queensland in 2006.

P. Wen

Dr Peng (Paul) Wen is a senior lecturer of control and computer engineering at the University of Southern Queensland. He is interested in the area of control and instrument, modelling and simulation, artificial intelligence, and biomedical engineering. He received his PhD, MS and BS degrees in 2001, 1986 and 1983, respectively, from the Flinders University of Southern Australia and Huazhong University of Science and Technology.