Delay Pattern Estimation for Signalized Intersections Using Sampled Travel Times

Abstract

Intersection delays are the major contributing factor to arterial delays. Methods to estimate intersection delay patterns by using measured travel times are studied. The delay patterns provide a way to estimate the delay for any vehicle arriving at the intersection at any time, which is useful for providing time-dependent intersection delay information to the driving public. The model requires sampled travel times between two consecutive locations on arterial streets, one upstream and the other downstream of a signalized intersection, without the need to know signal timing or traffic flow information. Signal phases can actually be estimated from the delay patterns, which is a unique feature of the proposed method in this paper. The proposed model is based on two observations regarding delays for signalized intersections: ( a) delay can be approximately represented by piecewise linear curves due to the characteristics of queue forming and discharging and ( b) there is a nontrivial increase in delay after the start of the red time that enables detection of the start of a cycle. A least-squares–based algorithm is developed to match measured delays in each cycle by using piecewise linear curves. The proposed model and algorithm are tested by using field experiment data with reasonable results.