Towards an agent-based framework for urban traffic congestion management Online publication date: Mon, 26-Oct-2020
by Sara Berrouk; Abdelaziz El Fazziki; Zakaria Boucetta
International Journal of Internet Technology and Secured Transactions (IJITST), Vol. 10, No. 6, 2020
Abstract: This paper introduces an integrated solution to the road congestion problem by modelling the road network, using real-time traffic data and drivers' parameters to compute the proposed congestion index for each road segment and generating recommendations to avoid the most congested trajectories. The proposed framework combines the benefits of the multi-agent systems, traffic data from static sensors and big data tools in order to optimise the traffic flow in urban areas. The congestion indexes are used in the road network generation which is represented by a weighted graph. The edges' costs are computed based on the congestion indexes and the edge's properties and vary when new traffic records are retrieved. In this study, the Hadoop framework is used in the data gathering and analysis along with an improved version of Dijkstra for the least congested path finding which allows the proposed framework to reach a higher level of performance.
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