Juan Alegre-Sanahuja
ABSTRACT
A variety of technologies can be applied to the collection and analysis of traffic data in smart cities. Vehicle detection, which is a fundamental aspect of traffic analysis, can be achieved by various technologies such as surveillance videos and loop detectors. This paper proposes a vehicle detection method that uses a set of sensors for bridge weigh-in-motion, which is an in situ nonintrusive method that avoids the disadvantages of other systems. In a practical implementation of this method, where data streams from sensors have to be processed in real time, we found vehicle-detection inaccuracies caused by the characteristics of signals from the sensors. To address these problems, we propose a simple and efficient method that uses two sensors and a wavelet transform. Our method improves the system accuracy by comparing the results of a robust wavelet-transform peak-detection technique applied to the signal streams from the two sensors. Experimental results demonstrate the high performance of this method, which can meet the accuracy requirements of realtime scenarios.
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Index Terms
- Wavelet transform based vehicle detection from sensors for bridge weigh-in-motion
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