An infrastructure-based approach for the Traffic Management problem in VANETs
Abstract
Expenses due to congestion problems in large urban centers amount to billions of dollars worldwide. This is due to time lost in traffic and fuel consumption caused mainly by traffic jams at peak times. Several works in the literature propose solutions to the traffic management problem using the processing, storage and communication capacity of vehicular networks. Among the solutions in the literature, infrastructural approaches utilize the processing and storage power of infrastructure to detect traffic jams and suggest vehicle routes. This paper presents GRIFO that, unlike the infrastructural approaches in the literature, vehicles are responsible for checking congestion and calculating new routes when needed. Using only information about near-road conditions provided by the auxiliary storage infrastructure, each vehicle verifies the need for recalculation. The proposed work manages to distribute the flow of vehicles in the road network in order to reduce the average travel time compared to literature algorithms.
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