Abstract
Traffic light control systems are commonly utilized to monitor and manage the flow of autos across multiple road intersections. Since traffic jams are ubiquitous in daily life, A crucial aim is to optimize the functioning of traffic signals for optimal traffic flow. Traffic light control systems aim to make sure automobiles flow smoothly along transit routes. However, considering the numerous parameters involved, synchronizing several traffic signal systems at neighboring junctions is a difficult challenge. Conventional systems are incapable of dealing with varied flows nearing intersections. Furthermore, the present traffic system does not account for reciprocal interference between nearby traffic signal systems, the asymmetry of automobile flow with time, accidents, the passage of emergency vehicles, and pedestrian crossings. This causes traffic congestion and jams. The goal is to provide an artificial intelligence-based method that enables adaptive management of traffic lights at an intersection to reduce traffic congestion in transportation. A simulation is also created to help visualize the problem and its solution. In this venture, an algorithm that enables adaptive control of congested crossings is presented to reduce traffic congestion in transportation networks. The algorithm modifies the optimal light timings to employ in the following cycle based on the number of cars in the junction and the rise in this number. To improve reliability, employing a doppler radar sensor to collect data from traffic is suggested. The transmitter pulses waves with the assistance of a doppler radar sensor, and the receiver listens for waves flowing back to the antenna as they strike objects in the atmosphere between each pulse. The distance between the antenna and the item (in this application, vehicles) may be measured simply by calculating the time it took for the wave to return to the antenna. The Doppler shift is used to illustrate the speed differential in traffic. The change in frequency or wavelength of a wave perceived by an observer moving relative to the wave's source is known as the Doppler shift. This is a common occurrence with sound and light waves. When the source of a wave approaches an observer, the frequency of the wave increases, resulting in a "blue shift." The frequency of the wave drops as the source moves away from the observer, resulting in a "redshift." As a result, the flexibility of each junction to select its signal lengths saves waiting times and guarantees that the intersection functions at peak performance. Keywords: Traffic control systems, intelligent traffic lights, modeling of traffic lights, traffic jam problems, reinforcement learning, doppler sensors.
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