Assistant Professor of Engineering Dr. Abolfazl Karimpour publishes collaborative research in Transportation Research Record
Transportation Research Record
Queue length at the intersections is one of the essential metrics required for the performance assessment of signalized intersections. The current methodology of estimating queue length in the literature suffers from several drawbacks, including unstable estimation and the requirement for multiple data sources. This study proposes a cycle-based maximum queue length estimation method based on: (a) the empirical observation of breakpoints in the time gap between successive actuations; and (b) the identification of queue status for all detector actuations in a cycle. The proposed method can help transportation agencies accurately estimate queue length at intersections with single-channel advance detection without the need for manual field data collection and without installing lane-by-lane detection.
Pudasaini, P., Karimpour, A., & Wu, Y.-J. (2023). Real-Time Queue Length Estimation for Signalized Intersections Using Single-Channel Advance Detector Data. Transportation Research Record, 0(0). https://doi.org/10.1177/03611981221151066