Optimizing traffic light signal timing using a yellow interval model: Methodology and empirical evaluation

Abstract

All over the world, especially in urban areas, the growing population and prosperity of the car industry have resulted in a steady increment in vehicles on the road, leading that already-built car-transportation infrastructure can not be commensurate with the traffic demand. Consequently, this will cause traffic congestion and thus a higher rate of traffic accidence. In such circumstances, the ability of traffic management becomes indispensable and crucial to ameliorate or even solve this problem. Although various advanced approaches can provide effective traffic management, the cost can be prohibitive to execute them pervasively. Many algorithms, especially machine learning related, require a mass of input data and a high hash rate. As a result, massive sensor systems, advanced computers, and elaborate programming will be unavoidable, which are costly. Two models in this paper, respectively, yellow light interval and traffic-light signalization, are based on summarizing and improving on previous models and are easy to understand and apply. The model focuses on timing the traffic light to maximize the number of vehicles passing through a traffic intersection in a given time. Many authors in their paper on traffic-light signalization hardly consider the effect of yellow light intervals. This paper provides a relatively comprehensive model of traffic-light signalization. Although the model in this paper is inferior to those advanced models utilized in effectiveness, this model can be applied simpler than others.