Construction of a traffic estimation model using dynamic response features extracted from SHM data in a cable-stayed bridge. (2017)

• Record Type: Journal Article
• Authors: Wattana, Kaiwan; Nishio, Mayuko
• Is Part Of: Procedia engineering. Volume 199(2017)
• Page Start: 2208
• Page End: 2213
• Publication Date: 2017
• Subjects: traffic volume estimation -- linear regression model -- dynamic response features -- response amplitude -- cable-stayed bridge; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2017.09.184
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: This paper presents the traffic volume estimation by constructing a statistical model using dynamic response features acquired in the structural health monitoring of an in-service cable-stayed bridge. The study started from the correlation coefficient analysis between some dynamic response features and the environmental and operational effects. It was found that the response amplitudes at several resonant modes were dominantly influenced by the traffic volume. The numerical analysis was thus conducted to understand the relationship between the traffic flow parameters; speed and density, and the bridge dynamic responses. The results showed that the sensitivity of acceleration amplitude to the traffic flow speed increased with increasing the traffic density. A linear regression model to estimate the traffic volume was then constructed using the training data. The explanatory variables were determined by a procedure that considered the correlation coefficients of possible features to the traffic volume and their multicollinearity. The constructed regression model showed the accurate fitting performance to the traffic data, and it was also capable of predicting both the traffic volume per five minute and the average daily traffic (ADT).