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In our previous work, we reported a system that monitors an intersection using a network of horizontal laser scanners. This paper focuses on an algorithm for moving-object detection and tracking, given a sequence of distributed laser scan data of an intersection. The goal is to detect each moving object that enters the intersection; estimate state parameters such as size; and track its location, speed, and direction while it passes through the intersection. This work is unique, to the best of the authors' knowledge, in that the data is novel, which provides new possibilities but with great challenges; the algorithm is the first proposal that uses such data in detecting and tracking all moving objects that pass through a large crowded intersection with focus on achieving robustness to partial observations, some of which result from occlusions, and on performing correct data associations in crowded situations. Promising results are demonstrated using experimental data from real intersections, whereby, for 1063 objects moving through an intersection over 20 min, 988 are perfectly tracked from entrance to exit with an excellent tracking ratio of 92.9%. System advantages, limitations, and future work are discussed.

In this research, a novel system for monitoring an intersection using a network of single-row laser range scanners (subsequently abbreviated as "laser scanner") and video cameras is proposed. Laser scanners are set on the road side to profile an intersection horizontally from different viewpoints. The contour points of moving objects are captured at a certain horizontal plane with a high scanning rate (e.g., 37 Hz). A laser-based processing algorithm is developed, thus the moving objects entered the intersection are detected and tracked to estimate their state parameters, such as: location, speed, and direction at each time instance. In addition, laser data and processing results are forwarded to an associated video camera, so that a visualization as well as fusion-based processing can be achieved. An experiment in central Beijing is presented, demonstrating that a large quantity of physical dimension and detailed traffic data can be obtained through such a system.