Novel computational intelligence-based model for effective traffic management in intelligent transportation system

Abstract

The evolution of intelligent transportation system (ITS) is essentially meant for upgrading the driving experience with more safety and accessibility of various analytical information from its extensive network. However, a significant gap is observed that doesn't cater up the complete demands of ITS. It has been also noted that computational intelligence (CI) based approach is slowly gaining pace in solving the transport related problems in ITS as compared to its other counterpart existing methodologies like artificial intelligence. The proposed manuscript introduces a novel computational framework towards assisting in relaying routing and navigational services using CI-based approach. A design of novel navigational controller unit is presented for global ITS scenario towards yielding an optimal decision of routing. The CI-based approach is implemented by integrating fuzzy process with evolutionary searching, learning and probability theory in most simplified form. The study also introduces a novel concept of relaying decision as feedback from navigational controller unit to specific vehicular node discretely unlike existing traffic controller system with an agenda to offer faster and effective clearance of queued vehicular nodes from target area. The study outcome shows higher consistency in its relay with better performance from existing study model in ITS.