<![CDATA[In an effort to provide solutions to traffic problems in urban areas, several methods such as fuzzy logic, Q-learning, neural networks, internet of things, and genetic algorithms are widely applied in answering this. In addition, these approaches emphasize the optimization function which will produce a traffic signal control design that can optimize the number of vehicles in a system which has implications for reducing waiting times and the volume of the number of vehicles in waiting conditions. The next impact of this is the possibility of achieving a reduction in the level of noise and pollution caused by motorized vehicles. Based on these things, a number of the methods mentioned earlier can be categorized as an approach in preparing a design or design oriented towards the built environment and in line with the goals of sustainable development. This study is an approach to review the mechanisms that can be developed by artificial intelligence in the traffic system so that it can adapt in real time towards the conditions around it.]]>
Copyrights © 2021
