A Constraint Optimization Algorithm for Automated Estimation of Turning Movement Counts at Signalized Intersections

Abstract

Accurate information on turning movements at signalized intersections is a critical requirement for many applications such as adaptive traffic signal control systems. A variety of sensor technologies have been developed for real-time traffic monitoring, such as loop detectors, traffic cameras, and radar; however, most of them are limited to provide link traffic information with few being capable of detecting turning movements. Several attempts have been made in the past to develop algorithms for inferring turning movements at intersections from entry and exit counts; however, the estimation quality of these algorithms varies considerably. This paper introduces a constraint optimization algorithm to estimate turning movements at signalized intersections. The new algorithm makes use of additional movement information available from the status of the signal heads at each phase to minimize estimation ambiguity. A simulation analysis is conducted on a four-leg, two-phase signalized intersection to evaluate the estimation performance of the proposed method. The results show that the algorithm is highly accurate and robust and fairly straightforward for real world implementation.