Hybrid intelligence model for traffic management in intelligent transportation systems

A typical traffic environment in an intelligent transportation system (ITS) involves various infrastructural units that generate a vast amount of sophisticated traffic data. Such a form of complex data is challenging to analyze and hence poses a potential issue in designing an effective and responsive traffic management system. Therefore, this paper develops an analytical modeling approach to harness the potential of artificial intelligence and computational intelligence. The scheme presents a simplified predictive approach that is meant to mitigate current issues and promote intelligent traffic management. The simulated outcome of the study showcases that the proposed scheme offers a significant advantage in its predictive performance in ITS.
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