On queue length estimation in urban traffic intersections via inductive loops

Queue length estimation in urban intersections represents a crucial issue for real-time traffic flows optimization. In this paper, we discuss different approaches to estimate the queue length using only inductive loops over two possible sensor layouts. Firstly, a model describing the queue dynamics is derived and a methodology to estimate the queue length at the preceding traffic light cycle is formulated, under the assumption of a single inductive loop sensor. Then, two strategies relying on a double-sensor layout are investigated to improve the quality of the queue length estimate, showing the potential of the use of a second inductive loop. The effectiveness of the proposed techniques is validated both on real-world data and through a microscopic traffic simulator, where real-world traffic profiles are employed.