Multivariate short-term traffic flow prediction based on real-time expressway toll plaza data using non-parametric techniques
by Annu Mor; Mukesh Kumar; Santanu Chaudhury
International Journal of Vehicle Information and Communication Systems (IJVICS), Vol. 7, No. 1, 2022

Abstract: Accurate real-time traffic flow prediction is a vital component of Intelligent Transportation System (ITS). The real-time traffic flow prediction helps transportation authorities as well as travellers for better route guidance. In this study, a novel approach is proposed for accurate Toll Plaza traffic prediction by introducing heterogeneous data sources other than traffic volume data. Toll data is analysed with exogenous factors such as weather conditions and holidays. Here, ten non-parametric techniques are applied for traffic prediction on real-time multivariate data set. The proposed approach is validated using data collected from Pinjore-Kalka Toll Plaza, Chandigarh, India. The performances of the non-parametric models are compared on the basis of mean square error, absolute mean square error, coefficient of determination and correlation. The experimental results revealed that random forest regression technique outperforms other techniques and achieved accuracy 90%. The proposed approach can be used for further proxy measure of Level of Service (LOS) to design the existing infrastructure more efficiently for the application purpose in smart cities.

Online publication date: Fri, 11-Feb-2022

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