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Article

REVIEW ON VEHICULAR SPEED, DENSITY ESTIMATION AND CLASSIFICATION USING ACOUSTIC SIGNAL

DOI: 10.7708/ijtte.2013.3(3).08


3 / 3 / 331-343 Pages

Author(s)

Prashant Borkar - Department of Computer Science and Engineering, G.H. Raisoni College of Engineering, Nagpur, India -

Latesh G. Malik - Department of Computer Science and Engineering, G.H. Raisoni College of Engineering, Nagpur, India -


Abstract

Traffic monitoring and parameters estimation from urban to non urban (battlefield environment) traffic is fast-emerging field based on acoustic signals. We present here a comprehensive review of the state-of-the-art acoustic signal for vehicular speed estimation, density estimation and classification, critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs). In recent years video onitoring and surveillance systems has been widely used in traffic management and hence traffic parameters can be achieved using such systems, but installation, operational and maintenance cost associated with these approaches are relatively high compared to the use of acoustic signal which is having very low installation and maintenance cost. The classification process includes sensing unit, class definition, feature extraction, classifier application and system evaluation. The acoustic classification system is part of a multi sensor real time environment for traffic surveillance and monitoring. Classification accuracy achieved by various studied algorithms shows very good performance for the ‘Heavy Weight’ class of vehicles as compared to the other category “Light Weight”. Also a slight performance degrades as vehicle speed increases. Vehicular speed estimation corresponds to average speed and traffic density measurement, and can be substantially used for traffic signal timings optimization.


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Acknowledgements:

Authors are thankful to the Director of GHRCE, for proving infrastructure to carry out research work and also to the anonymous reviewers for many helpful suggestions.


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