This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Traffic congestion on roads wastes travel times and increases fuel consumption as well as gas emissions which are dangerous to human health. This has led to growing concern about environmental protection and energy conservation and a number of studies to increase fuel economy and reduce gas emissions. To increase travel times so as to reduce fuel consumption and gas emissions, traffic signals at intersections must be well implemented. It is therefore necessary to employ the current technology of wireless sensor networks to enhance the optimisation of the signalised intersections so as to address such a concern. In this study, a vehicular traffic control model was developed to optimise a signalised intersection, using wireless vehicle detectors. Real-time traffic volume gathered were analysed to obtain the peak hour traffic volume causing congestion. The intersection was modelled and simulated in Synchro7 as an actuated signalised model using results from the analysed data. The model for morning peak and evening peak periods gave optimal cycle lengths which result in the reduction of gas emissions, fuel consumption and delay at the intersection.
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