Acoustic Signals for Traffic Density State Estimation and Its Applications
A Design and Development Approach
(Sprache: Englisch)
As the number of vehicles in urban areas is ever increasing, it has been a major concern of city authorities to facilitate effective control of traffic flows in urban areas. In this context, Vehicular traffic density state estimation provides an important...
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As the number of vehicles in urban areas is ever increasing, it has been a major concern of city authorities to facilitate effective control of traffic flows in urban areas. In this context, Vehicular traffic density state estimation provides an important information for road planning, intelligent traffic routing, adaptive traffic signal control, etc. The Traffic Density State estimation is fast emerging field based on an acoustic signal. Developing geographies like Asia where the traffic condition is chaotic and non-lane driven, intrusive techniques may be inapplicable. The traffic density state condition at any location is depends upon the mixture weighting of spectral components of various vehicular acoustics. This book considers the problem of vehicular traffic density state estimation using statistical framework that uses the cumulative acoustic signal from a roadside installed microphone, to classify the vehicular traffic density into Low (free flow) state, Medium flow state, Heavy state etc. and various application based on it.
Autoren-Porträt von Prashant Borkar
Borkar, PrashantDr. Prashant Borkar is PhD in Computer Science and Engineering. His research interest includes Soft Computing, Optimization, Intelligent Transport Systems and Data Science. He is recipient of Best Teacher Award & currently working as In-charge CoE, Data Science and In-charge MIS. He has more than 40 Publications in reputed Conferences and Journals.
Bibliographische Angaben
- Autor: Prashant Borkar
- 2020, 176 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6200564639
- ISBN-13: 9786200564634
Sprache:
Englisch
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