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Title: Online state and multidimensional parameter estimation for a macroscopic model of a traffic junction
Authors: Chetcuti Zammit, Luana
Fabri, Simon G.
Scerri, Kenneth
Keywords: Expectation-maximization algorithms
Traffic engineering -- Data processing
Intelligent transportation systems
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Zammit, L. C., Fabri, S. G., & Scerri, K. (2017). Online state and multidimensional parameter estimation for a macroscopic model of a traffic junction. 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama. 1-6.
Abstract: An online multidimensional self-estimation algorithm is developed to jointly estimate the parameters of a macroscopic model describing the traffic dynamics in a signalized junction under different traffic conditions, together with the state variables characterising traffic flow. The proposed novel methodology is based on the Expectation-Maximization algorithm and multidimensional Robbins-Monro stochastic approximation. The algorithm is validated on the geometry of a signalized 3-arm junction within the traffic network of Malta resulting in a mean percentage error of -0.965% on the parameter estimates. This is aimed to form part of an adaptive control loop for traffic light systems that is able to autonomously adjust to changing traffic conditions.
Appears in Collections:Scholarly Works - FacEngSCE

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