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Aims and background: The integration of communication tools has allowed for effective decision-making in smart cities and Internet-of-Things (IoT). One major issue that people who commute to cities everyday encounter is traffic congestion. Thanks to the progress and backing of ICTs, transportation solutions have been designed and implemented, leading to the development of ITSs and the provision of numerous innovative services. Objectives and Methods: These services include ones that guarantee safety, provide drivers with useful information, enable greater street movement, and avoid congestion, among many others. In industrialized nations, traffic data is collected by specialized sensors that can anticipate future patterns. Commuters are kept informed of any traffic updates through the Internet. When there is little or no physical infrastructure and Internet connection, these methods become unworkable. Internet access is still a problem in rural regions, and there are no roadside units in underdeveloped nations. This article presents an architecture for smart cities' intelligent vehicular networks that can impromptu accept data from nearby vehicles in real time and use it to choose routes. As embedded devices in vehicles, we utilized Android-based smartphones with Wi-Fi Direct capabilities. To set up our smart transportation system, we utilized a vehicular ad hoc network. Results: Data was collected and processed using separate methods between two major cities in a developing nation. Resource utilization, transmission delay, packet loss, and total trip time were measured against several fixed- and dynamic-route-selection algorithms to assess the framework's performance. Conclusions: When equated to a conventional fixed-route-selection procedure, our results reveal a 33.3% reduction in trip times.
Sesadri et al. (Fri,) studied this question.