With the emergence of Artificial Intelligence (AI) and the growing expectations of the role its emerging technologies can play in effectively tackling transportation system challenges, the integration of AI technologies into urban transportation systems has garnered increased attention. This is due to their capabilities to process and analyze vast amounts of data in real-time and the anticipated potential of AI as a promising means to tackle traffic congestion and improve vehicle routing in urban areas. By harnessing the power of AI, it becomes possible to develop smart systems that dynamically adapt to traffic conditions, thereby enhancing transportation efficiency, reducing congestion-related issues, and promoting sustainable urban development.
Accordingly, as part of the efforts of Naif Arab University for Security Sciences, this report aims to explore the potential of employing AI techniques to reduce congestion rates on roads in Arab cities. The report delves into the intersections between AI and urban transportation, with a particular focus on improving vehicle routing and alleviating traffic congestion in the Arab region. The primary objective is to uncover the most important AI techniques and algorithms related to the field of transportation and the opportunities for their application and utilization in designing transportation policies for the Arab region that reduce congestion rates, shorten travel times, and contribute to road safety. This report is based on a systematic review of published research literature on papers related to the problem of traffic congestion and AI techniques used in measures to reduce it.
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