Real-Time Prediction of Queues at Signalized Intersections to Support Eco-Driving Applications
Project Title
Real-Time Prediction of Queues at Signalized Intersections to Support Eco-Driving Applications
University
Old Dominion
Principal Investigator
Mecit Cetin, Ph.D.
Assistant Professor, Old Dominion University
PI Contact Information
Funding Sources and Amounts Provided
US Department Of Transportation $40,000
Old Dominion University $40,000
Total Project Cost
$80,000
Agency ID or Contract Number
DTRT12GUTC17
Start Date
5/1/12
End Date
9/30/14
Description of Research Project
The overall objective of this research is to develop models for predicting queue lengths at signalized intersections based on the data from probe vehicles. The time and space coordinates of the probe vehicles going through signalized intersections are utilized to predict the back of the queue profile. For a single intersection, prediction models are developed where both over-saturated and under-saturated conditions are considered. The shockwave theory (i.e., the Lighthill-Whitham-Richards theory) is used to estimate the evolution of the back of the queue over time and space from the event data generated when probe vehicles join the back of the queue. An analytical formulation is developed for determining the critical points required to create the time-space diagrams that characterize queue dynamics. These critical points are used to estimate the queue lengths. The formulation was tested on the data obtained from traffic simulation software VISSIM. It was found that the shockwave-based formulation is effective in estimating queue dynamics at signalized intersections for under- and over-saturated conditions even with a relatively low percentage of probes (e.g., 10-20 percent) in the system. For example, under the oversaturated conditions simulated, the error is less than ±10 percent in more 90 percent of the cycles when the market penetration of probe vehicles is 15 percent.
Implementation of Research Outcomes
The queue estimation methods developed in this study are implemented in a micro simulation environment. The simulation results show the proposed models are effective in estimating queue lengths even when the market penetration of probe vehicles is relatively low.
Impacts and Benefits of the Project
The proposed methods were tested on the data obtained from traffic simulation software VISSIM. It was found that the shockwave-based formulation is effective in estimating queue dynamics at signalized intersections for under- and over-saturated conditions even with a relatively low percentage of probes (e.g., 10-20 percent) in the system. For example, under the oversaturated conditions simulated, the error is less than ±10 percent in more 90 percent of the cycles when the market penetration of probe vehicles is 15 percent.
Papers
- S. Rompis, F. Habtemichael, and M. Cetin, “Calibrating Simulation Models for Traffic During Incidents Using Shock Wave Speeds Estimated from Field Data” The 94th Annual meeting of the Transportation Research Board, Washington, D.C., January 11-15, 2015.
- M. Cetin and H. Rakha “Estimating Fuel Consumption at Signalized Intersections from Probe Vehicle Trajectories” Presented at the 93rd Annual meeting of the Transportation Research Board, Washington, D.C., January 12-16, 2014.
- O. Unal and M. Cetin “Estimating Queue Dynamics and Delays at Signalized Intersections from Probe Vehicle Data” Presented at the 93rd Annual meeting of the Transportation Research Board, Washington, D.C., January 12-16, 2014.
Presentation
- M. Cetin and H. Rakha “Estimating Fuel Consumption at Signalized Intersections from Probe Vehicle Trajectories” Presented at the 93rd Annual meeting of the Transportation Research Board, Washington, D.C., January 12-16, 2014.
- O. Unal and M. Cetin “Estimating Queue Dynamics and Delays at Signalized Intersections from Probe Vehicle Data” Presented at the 93rd Annual meeting of the Transportation Research Board, Washington, D.C., January 12-16, 2014.
Web Links
Final Report: ODU_TranLIVE_Final Report_Real-Time Prediction
Keywords
- queue length estimation
- probe vehicles
- eco-driving
- fuel consumption
- signalized intersections