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Omniscient Situational Aware Traffic Management System (TMS) for Smart Cities
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 35 |
| Year of Publication: 2022 |
| Authors: Iqbal Ahmed, Riya Biswas |
10.5120/ijca2022922420
|
Iqbal Ahmed, Riya Biswas . Omniscient Situational Aware Traffic Management System (TMS) for Smart Cities. International Journal of Computer Applications. 184, 35 ( Nov 2022), 14-20. DOI=10.5120/ijca2022922420
Abstract
Modern and efficient modes of transportation play a crucial role in development of any society. Emerging technologies, especially, Internet of Things (IoT) are leading the world towards Smart Cities. However, Smart Cities cannot function without an intelligent and autonomous Traffic Management System (TMS). Smart Cities require such TMS, which is not hindered by issues like, on-road congestion and delays, accidents, inappropriate emergency response, waiting/searching or in extreme cases unavailability of parking. Those all factors also contribute to the wastage of fuel and energy and are the major source of air pollution in urban areas. Vehicular Ad-hoc Network (VANET) can utilize the full potential of the IoT and might provide a comprehensive solution for traffic related problems in Smart Cities. Therefore, we offer a VANET based Novel Quasi Omniscient Situational Aware Traffic Management System (TMS) that expeditiously tends to eliminate all these traffic-related problems. The System acquires user, vehicular and environmental contexts through road- side sensors, then optimally processes and stores it either at edges or at cloud layer (according to the situation) and produces requisite actuations. It recommends the optimal path from source to destination and automatically reserves the (optimal) nearest parking spot to destination while considering the dynamic real-time variables in the environment such as congestions and road-blockages throughout the itinerary. Simultaneously, we have created an analogy between vehicle and packet routing using Particle Swarm Optimization (PSO) method. System routes and manages the vehicles, as packets are (optimally) routed and guided over the IP network.
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