Citation

Yao J, Tang K. Transp. Res. C Emerg. Technol. 2019; 109: 1-18.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trc.2019.10.003

PMID

unavailable

Abstract

Queue length is vitally important for signal control optimization and congestion management of urban arterials. Due to the existence of mutual influence of neighboring intersections, cycle-by-cycle estimation of queue length under spillover conditions remains a challenging problem given low-resolution detector data. On most urban arterials in China, point detectors are commonly installed at the intersection approaches and the upstream segments, providing volume, occupancy and speed data at a time interval of 1 min, i.e., a double-section low-resolution detection environment. Thus, the objective of this study is to propose a method to estimate the cycle-based queue length at signalized intersections considering spillover in the context of the above detection environment. Considering dense traffic conditions, uniform distribution is used to transform the low-resolution volume data into vehicle arrivals in 1 s. To deal with spillover conditions, mutual effects of neighboring intersections are classified into four different cases, based on the offsets between the neighboring intersections. Detector data at the upstream intersection approach are used to modify the volume data of the downstream intersection when long queue occurs, and the effect of spillover can thus be formulated analytically using the shockwave theory. Finally, the queue length can be calculated by accumulating queue lengths of all offset conditions within a cycle. Evaluation is done through an empirical case of two intersections, and a simulation case of seven intersections.

RESULTS show that the accuracy can reach 85.1% and 82.4% respectively. In both cases, spillover cycles can be recognized with stable and reliable performance.

Language: en

Keywords

Low-resolution detector data; Queue length; Queue spillover; Shockwave theory; Signalized intersection