Smart Traffic Controller

Controls traffic at intersections using a camera and camera vision. Reduces the need for sensors and helps to make college campuses safer by clearly defining the right of way on roads.

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Inspiration

We noticed how poorly traffic is controlled on TAMU campus and researched more about the issue. Increasingly traffic and car control has become an issue on campuses across the country, and with our smart traffic controller we have a solution to mitigate the right of way issues seen on college campus streets.

What it does

It identifies people and whether or not they are crossing an intersection. If they are attempting to cross it will tell cars/vehicles to not pass on the intersection.

How we built it

We utilized computer vision with a YOLO model ID people and track their movement across the camera's vision.

Challenges we ran into

We attempted to utilize a Raspberry Pi to prove our system could work on discrete units that could be set up at already existing intersections. However, we ran into issues when it came to setting up the raspberry pi and were unable to complete that portion of our project.

Accomplishments that we're proud of

Persevering through frustrating moments of technology not working, and producing an end product even in spite.

What we learned

How AI technologies can be applied to make college campuses safer.

What's next for Smart Traffic Controller

-Increasing the effective distance of the camera -Utilizing a better model for our application (detect people from the top).

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