Real-time estimation of turning movement counts at signalized intersections using signal phase information

• We propose a method to determine turning movement counts at signalized intersections.
• The method makes use of signal phase information and entry/exit volumes.
• The algorithm is able to estimate both constant and varying turning counts.
• The results show the proposed phase-based estimation method is robust and accurate.
• The algorithm outperforms the cycle-based least-square and optimization methods.

A variety of sensor technologies, such as loop detectors, traffic cameras, and radar have been developed for real-time traffic monitoring at intersections most of which are limited to providing link traffic information with few being capable of detecting turning movements. Accurate real-time information on turning movement counts at signalized intersections is a critical requirement for applications such as adaptive traffic signal control. 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 method to improve accuracy and robustness of turning movement estimation at signalized intersections. The new algorithm makes use of signal phase status to minimize the underlying estimation ambiguity. A case study was conducted based on turning movement data obtained from a four-leg signalized intersection to evaluate the performance of the proposed method and compare it with two other existing well-known estimation methods. The results show that the algorithm is accurate, robust and fairly straightforward for real world implementation.