The main contribution of this paper is a comparison of different machine learning algorithms for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard using measurements of road surface vibrations and magnetic field disturbances caused by vehicles. The algorithms considered are logistic regression, neural networks, and support vector machines. They are evaluated on a large dataset, consisting of 3074 samples and hence, a good estimate of the actual classification rate is obtained. The results show that for the considered classification problem logistic regression is the best choice with an overall classification rate of 93.4%.
Comparison of Machine Learning Techniques for Vehicle Classification Using Road Side Sensors
2015-09-01
211543 byte
Conference paper
Electronic Resource
English
Road vehicle classification using machine learning techniques
British Library Conference Proceedings | 2019
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