Road Traffic Optimization for Mid-sized African Cities – Application of Fuzzy Algorithms and Computer Vision

Abstract

Traffic congestion in urban areas is a global challenge - leading to stifled economic growth, increased road accidents and atmospheric pollution, among other negative trends. Existing traffic management solutions have proven to be largely ineffective in medium-size African cities. Wireless sensor networks have emerged as possible cost-effective solutions, especially in under-developed countries. In this paper, we present a solution for detection and quantification of traffic congestion at signaled isolated four-way junctions in order to optimize traffic flow. The research utilizes optical sensors to collect road parameters and fuzzy logic to quantify and then prioritize entry. Simulations are used to compare strategies employed by traffic signals; the interest being to observe which of the two traffic light management schemes is more effective. The two schemes compared in this paper implement fairly weighted round-robin and fuzzy algorithms.