Queue length estimation for a metered on-ramp using mesoscopic simulation

Abstract

This paper proposed an analytical method for queue length modeling at a metered on-ramp, and developed a mesoscopic simulation model for queue length estimation under various demand-to-capacity scenarios. Queue length data were collected at four representative ramp metering locations for model validation; results showed that the queue length modeling method could properly capture the realistic queue profile, and the estimated queue lengths were close to the field observations. It was found that for under-saturated scenarios, queue length showed an exponential increasing trend with demand-to-capacity ratio; while for over-saturated scenarios, the queue length tended to increase linearly with demand-to-capacity ratio. Simulation results indicated that for under-saturated conditions, the required queue storage length was approximately 5.7 percent of on-ramp demand when demand was less than 500 vphpl, or 3.9 percent when demand was between 500 and 900 vphpl.

Keywords:

• Ramp metering
• queue length modeling
• mesoscopic simulation
• demand-to-capacity ratio
• queue storage length

Acknowledgements

The authors thank Dr. Zhongren Wang from Caltrans Headquarter and Arafat Khan from University of Nevada, Reno (UNR) for their constructive comments and discussions; Yue Zhao and Anabel Hernandez from UNR for help with field data collection and extraction.