Real-time queue estimation model development for uninterrupted freeway flow based on shockwave analysis

Abstract

In this study, the authors developed a time-space discrete macroscopic model based on the shockwave theory for real-time queue estimation in uninterrupted freeway flow, using fixed-location loop detector data. After investigating the queue characteristics both at an active bottleneck and within a variable speed limit control case, the proposed model was applied to these two cases on Whitemud Drive, a major freeway corridor in Edmonton, Alberta, Canada. Modified Highway Capacity Manual–based methods were used to determine queue density in uninterrupted freeway flow. The effect of time interval size on queue estimation was studied, as loop detector data acquisition frequencies may differ. It was found that the proposed model accurately estimates real-time queue length independent of the time interval. Multiple single queues were implemented in a calibrated VISSIM 5.3 micro-simulation model to perform the validation task. The study is a helpful foundation for future active traffic management strategy development and improvement.