Abstract
The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application a feature vector containing 48 parameters was extracted and analyzed in the context of parameter separability and classification effectiveness employing SVM (Support Vector Machine) algorithm. In conclusion, the classifier developed and its effectiveness were discussed.
Highlights
An important element of the environment management is checking and controlling pollution of various types, including noise
A Support Vector Machine (SVM) algorithm was used to carry out the classification tests
The results are shown with the use of true positive and false positive measures as we are interested in the extent to which true positives are not missed, so false negatives are few and the extent to which positives really represent the case evaluated
Summary
An important element of the environment management is checking and controlling pollution of various types, including noise. Acoustic noise maps show the noise level imposed on existing geophysical maps of cities, areas around railway junctions, etc. Such a presentation of data allows for determining the area in which the sound level of passing vehicles can be a problem for the environment. Traffic monitoring is based on the determination and interpretation of noise maps, and on the analysis of its structure
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