Transportation by vehicle is becoming more and more important everywhere, particularly in large urban areas. The continual technological advancements that support vehicle mobility, such as controlled electrical, inductive rings, monitoring cameras, and so forth, are expensive and in addition demand significant maintenance costs. Moreover, the accuracy of these devices is also dependent on the weather. The standard usual approaches aim to simplify signalized intersections operation for a certain traffic arrangement and thicknesses. In any event, a major barrier to using these tactics is the difficulty of consistently displaying the effective behaviour of changing configurations and traffic volumes. By many accounts, traffic is more of a transition than an improvement problem. In order to address the aforementioned problem, we offer a method in this study that performs flexible signal timing management using a setup of a distant sensor nodes. The goal of the study is to investigate methods for creating a developing this system that can integrate and enable some of the most recent traffic signal technologies and, as a result, reduce the amount of time that cars are typically stopped at a junction. The suggested algorithms can adapt to the traffic flow at any intersection of streets. To construct a graph of typical noise levels versus cycles, transportation incidents from real life are acted out in the Green Arrow District Sim, a stage that has been faithfully replicated. The results obtained demonstrate the viability of the suggested method for the stop light at a real street cross location.
Internet Traffic Dynamics in Wireless Sensor Networks
2023-05-12
1490916 byte
Conference paper
Electronic Resource
English
Sparse Vehicular Sensor Networks for Traffic Dynamics Reconstruction
Online Contents | 2015
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