The Role of Artificial Intelligence in Traffic System Management of Smart Cities: A Comprehensive Review

Abstract

High rate of urbanization in the twenty first century has created transportation related problems hitherto unknown to human history such as increased levels of traffic, automobile emissions, and ineffective transport systems. In retaliation, these advocates propagate the idea of what could be called the smart city, an urban paradigm, which utilizes state-of-the-art technologies to address such problems on a systematic level. Based on the real-time proposal making, prediction analytics, and automation of infrastructures, modernization of traffic nowadays is driven by artificial intelligence (AI). Thus, the current use of AI in regulation of traffic is reviewed in the paper, with the focus being put on such fields as intelligent traffic signals control, predictive traffic modeling, autonomous vehicles, traffic incident identification, and improvement of a public transportation network. Some of the main AI methods, such as machine learning, deep learning, reinforcement learning, and computer vision, are subject to close review in the context of urban transport. Examples from different counties are discussed, and infrastructural limitations, security to privacy information, and ethical awareness have also been looked into. The conclusion poses the emergent questions and future research direction of the topic of intelligent, AI-based traffic systems as it heads towards sustainability and smart-city assimilation.