Analysis of Downstream Queues on Upstream Capacity Expansion of Urban Signalized Intersection

Abstract

AbstractSignalized intersection is a fundamental component of an urban transportation system and appropriate treatments for intersection related congestion and safety issues are increasingly growing in importance. The most direct and intuitive approach to alleviate the recurring congestion is to cope with the peak hour disparity between travel demand and supply at the bottleneck intersections by expanding intersection capacity. However, intersection treatments such as adding lanes, turning movement restrictions, and grade separation that were traditionally applied to improve intersection capacity may not realize the expected benefits of relieving congestion and reducing delay as the traffic conditions at the downstream intersections can be greatly deteriorated by increased upstream arrivals. Additionally, the extended queue generated from downstream intersections can spill back into the upstream intersection and diminish the performance of the upstream treatment. This phenomenon is frequently observed in large urban areas where the traffic volume is heavy, intersection spacing is short and cycle length is long. This study was conducted to provide traffic engineers with a simple, practical and step-by-step analysis method to identify the occurrence and the type of queue spillback (Cyclic and Sustained), to determine the effects of downstream queues on upstream capacity, and to select the best capacity expansion treatment. The theory and methods for measuring the consequence of downstream queue effects and quantifying the potential capacity cutoff are developed based on the updated queue size and intersection capacity estimation methodologies for signalized intersections in the Highway Capacity Manual 2010 (HCM 2010). A spreadsheet-based computational tool was developed to assist in the process of capacity constraint identification and calculation. A case study is presented to demonstrate the practical use of the analysis method.