The project suggests and designs a real time traffic control system to solve the traffic congestion problem and meet the desire of vehicle drivers.
This system will be distributed on the road network and will continuously collect traffic information (using Bluetooth), analyze it, and provide real-time plans to traffic lights that ensure optimal travel time for all drivers.
Roads congestion bother us all of the time. Despite the drivers’ desire to get a “green wave” and go through the fastest way to their destination, the current traffic control system does not allow this, because it has preset programs that do not allow quick adaptation to developed situations on the road.
Most of the new vehicles include Bluetooth-based hands-free and media systems, either pre-installed by the vehicle’s manufacturer, or a third-party system installed by the vehicle’s owner. These Bluetooth systems are usually visible, and scan for smartphones or other Bluetooth devices to connect to them.
By exploiting this fact, it is possible to place at junctions sniffing units that will scan for Bluetooth-enabled vehicles and get their MAC addresses. Since the MAC address is unique, it allow us to build a database of traffic information that tells us which vehicles went through each node at any given time.
This information is then sent to a centralized cloud, from which a server computer can gather information on the entire urban area. Using machine learning algorithms and programs, it will control the traffic lights to optimize the traffic flow through each junction and path. Optionally, it might even offer information about the best path to the driver.
What characterizes such a system is automation – it requires no intervention from any side after it is installed. In addition, wide distribution at junctions all around the city, will allow real-time response that take into account other junction states as well.
Moreover, it’s relatively cheap and allows identification of special vehicles to prioritize through their MAC address (police cars, ambulances, public transit).
