Techniques for Smart Traffic Control: An In-depth Review

Inadequate space and funds for the construction of new roads and the steady increase in number of vehicles has prompted scholars to investigate other solutions to traffic congestion. One area gaining interest is the use of smart traffic control systems (STCS) to make traffic routing decisions. These systems use real time data and try to mimic human reasoning thus prove promising in vehicle traffic control and management. This paper is a review on the motivations behind the emergence of STCS and the different types of these systems in use today for road traffic management. They include – fuzzy expert systems (FES), artificial neural networks (ANN) and wireless sensor networks (WSN). We give an in depth study on the design, benefits and limitations of each technique. The paper cites and analyses a number of successfully tested and implemented STCS. From these reviews we are able to derive comparisons of the STCS discussed in this paper. For instance, for a learning or adaptive system, ANN is the best approach; for a system that just routes traffic based on real time data and does not need to derive any data patterns afterwards, then FES is the best approach; for a cheaper alternative to the FES, then WSN is the least costly approach. All prove effective in traffic control and management with respect to the context in which each of them is used.