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Lookup NU author(s): Abraham Narh,
Dr Graeme Hill,
Dr Neil Thorpe,
Professor Margaret Carol Bell CBE
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Current signal control systems for managing traffic in urban areas cannot take into account the spatial and temporal evolution of congestion across network regions within cities. This inhibits these systems’ ability to detect reliably, on a strategic level, the onset of congestion and implement effective preventative action through adjusted traffic signal settings. Chaos Theory, however, is capable of analysing and forecasting time-dependent non-linear systems and is therefore a prime candidate for application to urban traffic control to improve the management of congestion and pollution. This paper describes the application of Chaos Theory to identify the dynamical state of urban road networks, and presents results based on analysis of a network of interconnected signalised junctions in Leicester. Traffic flow data from SCOOT at 20 second time resolutions were analysed using the Phase Space Reconstruction method. The Lyapunov exponents based on the flow variables indicate the network’s cyclical dynamical states (i.e. unstable, asymptotic and steady), thus identifying the level of congestion. This research suggests that incorporating chaos-based algorithms in existing UTC systems to trigger optimum control strategies that are one-step ahead of real-time traffic congestion, rather than being one-step behind, could radically improve strategic management of traffic playing an important role in improving air quality.
Author(s): Narh A, Hill G, Thorpe N, Bell M
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 46th Annual UTSG Conference
Year of Conference: 2014