Some agencies use cameras to monitor traffic modes, but cameras are limited in rainy, dark or foggy conditions. Some cities use radar instead of cameras, which works better in low-visibility but typically can’t provide as rich a picture of what’s going on. Conventional radar gives movement and position data for all approaching entities, but it’s very hard to tell the difference between modes with any reliability.

In the latest report funded by the National Institute for Transportation and Communities (NITC), Development of Intelligent Multimodal Traffic Monitoring using Radar Sensor at Intersections, researchers Siyang Cao, Yao-jan Wu, Feng Jin and Xiaofeng Li of the University of Arizona have tackled the issue by developing a high-resolution radar sensor that can reliably distinguish between cars and pedestrians. This sensor also supplies the counts, speed, and direction of each moving target, no matter what the lighting and weather are like.
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