Abstract
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Low resolution camera already install throughout the United States can be used as a way to better resolve irregular traffic flow within a given area. This could possibly be of interest to civil engineers and law enforcers in order to get traffic problems resolved quickly as possible and possibly reduce the amount of personnel needed for a job at a given time or even automate certain tasks when possible.
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Introduction
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Web cameras used today can be used to record normal traffic patterns within a given location. This data can then be used to teach a system what normal traffic flow is within a given time and traffic lights could be automated to change timings when traffic flows falls below or above the norm. This could potentially help redirect traffic flow early enough so that the system avoids a potential problem in the future.
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Methods
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Data is collected in certain chunks of time and the average amount of vehicles visible on the screen on a given street is collected and observed. The data is categorized by the day and time segments. The actual data collection will be done by human observation of the pictures to eliminate false positives.
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Results
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So far with the data recorded, it has shown that the highest congestion of cars occurring during the rush hours of businesses. However, lunch hours tend to depend on the area being recorded because of some areas tend not to be hot spots for lunch breaks. Times Square was the only example of high congestion and standing wave effects, but since Times Square normally deals with high traffic, it was managed fairly well.
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Privacy
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Not many privacy issues arose with this study since the cameras used use camera angles that make individual people hard to identify and license plate numbers hard to see. This is due to the use of low resolution cameras. It may be possible to identify individuals with the use of better cameras but in this case it was not a problem.
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References
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Camera:https://www.amasci.com/amateur/traffic/traffic1.html
Camera:https://www.sciencenews.org/pages/sn_arc99/7_3_99/bob1.htm
Project Paper (PDF)
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