Methods Results and Discussion
With the solution deployed in the field, anonymised detection data was collected at the above locations whenever the devices were powered. This meant full days for the devices in locations L1 to L3, as they are on a permanent grid, and around 10 hours per day for the devices in locations L4 to L9, as they are on a switched grid tied to the public lighting schedule. Our approach to evaluate traffic counting was done by calculating median values per hour per weekday (Figure 1 and S2). Observations In terms of image quality, a first observation is that the reduced visibility at night did not affect the viability of the solution. It did degrade the quality of the camera’s video stream, producing video frames with much more noise than during the day, but still allowing for detections to be made. This image degradation was better or worse depending on the lighting conditions at each location, with locations with High-Intensity Discharge (HID) lamps, especially sodium-based ones (both HPS and LPS) produced the most degraded streams. Before diving into the details of the results, we observed some general trends that, although expected, should be mentioned.
1. 2. 3.
There is a significant reduction in traffic volume during nighttime hours, a trend that aligns with expectations for residential zones and their access roads, such as those under study.
There is less traffic at weekends and during holidays. This difference is smaller than that observed between day and night, but the trend is clear.
Rush hour traffic is very common in cities and their suburbs and is quite noticeable in the data collected at all locations. Data shows a peak in traffic for a period in the morning (from 7 am to 9 am) and in the afternoon (from 4 pm to 7 pm).
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