Real-Time Queue Length Estimation at Signalized Intersections

Abstract

In order to accurately and rapidly estimate vehicle queue length at signalized intersections, the basic assumption is made that traffic flow in transition is divided into two parts on the basis of traffic queue process analysis and the survey data. Then, the real-time queue length estimation model is formulated and the parameter calibration is proposed. The equivalent queue length model is developed. The models are validated by the field data from the cities of Dalian and Changchun in China. The results indicate that the average relative errors between the estimated and observed queue lengths are 6.22% and 7.95%, respectively. Moreover, the equivalent queue lengths are all longer than the observed ones for congested traffic. The new method can be easily implemented and is applicable to address the vehicle queue length estimation under the other situations.