Traffic flow estimation using acoustic signal. (September 2017)

• Record Type: Journal Article
• Authors: Lefebvre, Nicolas; Chen, Xiandong; Beauseroy, Pierre; Zhu, MengYao
• Is Part Of: Engineering applications of artificial intelligence. Volume 64(2017:Apr.)
• Page Start: 164
• Page End: 171
• Publication Date: 2017-09
• Subjects: Support vector regression -- Audio signal processing -- Zonal Kernel -- Urban data -- Traffic estimation; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2017.05.019
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The standard approaches of road traffic flow measurement as a part of advanced traffic management system relies on data acquisition from inductive loops or visual detectors. Due to their high cost and a number of operational limitations, this study was to elaborate a new concept of traffic flow estimation based on data from acoustic sensors. The experimental study has been conducted on a roadside of Paris ring-road (peripherique boulevard) during 11.5 days. The obtained data has been processed with help of Support Vector Regression method. The performances of the proposed solution have been assessed against standard traffic flow measurements. Obtained result show that this approach is promising and has potential of usage as independent measurement system and as auxiliary unit for existing systems.