Analysis of Roundabout Performance by Modelling Approach Flow Interactions

Aerial photograph of road

Abstract

An analytical method for estimating roundabout entry lane capacity and performance measures is presented. The method is based on modelling the gap acceptance process that takes place in real-life roundabout operation. Unlike past studies that treated roundabouts as a series of T-junctions, the method presented here allows for approach flow interactions. A factor is used to adjust the basic gap-acceptance capacity for the effects of the origin-destination pattern and the queueing characteristics of the approach flows. Circulating stream characteristics are determined considering the approach lane use characteristics of the traffic streams that constitute the circulation flow. The modelling of interactions amongst approach flows is important, especially in heavy and unbalanced demand flow cases. Ignoring approach flow interactions can cause serious overestimation of capacity, and underestimation of delays and queue lengths, especially for multi-lane roundabouts with unbalanced flow patterns. This demonstrated through a case study that compares the results from the methods with and without approach flow interactions. Formulae are presented for the estimation of stop-line (control) delay, queue length, as well as proportion queued, queue clearance time and queue move up rate. The formulae were derived and calibrated using the two-term model structure based on the overflow queue concept as used in the well-established method for signalised intersections. The formulae also allow for the effects of any initial queued demand at the start of the analysis period. The difference between the cycle- average queue and the average back of queue is emphasised.

Reference

AKÇELIK, R., CHUNG, E. and BESLEY M. (1997). Analysis of Roundabout Performance by Modelling Approach Flow Interactions. Proceedings of the Third International Symposium on Intersections Without Traffic Signals, July 1997, Portland, Oregon, USA, pp 15-25.

Registration open for online training in May and June 2024. Learn more..