Development of degree of saturation estimation models for adaptive signal systems

Abstract

Throughout the world, several areawide traffic control systems have been developed and implemented. The degree of saturation plays a crucial role for the optimization of signal control variables. This paper investigates an alternate way to estimate the degree of saturation. From a correlation analysis, a strong positive linear relationship was found between percent occupancy time and degree of saturation. Based on this result, a linear regression model was constructed. In addition, a new model was also suggested for the use of traffic control systems. This paper also presents comparative results on degree of saturation models adopted in several adaptive traffic control systems. Each model was tested and evaluated using field data in terms of estimation errors. From the results, it was observed that SCOOT and SCATS models produced better estimates than other models under the light flow conditions. Both the new and regression models underestimated slightly for all periods, whereas the Barcelona model overestimated consistently. Under the heavy flow conditions, however, the new model showed improved performance over the other models.