An Integrated Framework For Intelligent Parking By Using Opto Neural Mechanism

Abstract

Our country has developed rapidly for decades with lot of commercial buildings and well-contacted roads and growing number of vehicles. The transportation industry has also become the backbone of the economy because of its widespread use in trade and commerce. Therefore, parking the vehicles has become a consideration. When parking the vehicles in a parking space, old parking system is still used which is maintained in an unplanned mode and without any discipline. Because of this, people usually park their cars wherever they want, which can be a mess because most people don t follow any discipline. An issue of parking space is a serious concern in some locations, especially shopping complexes, hospitals, buildings and other buildings that requires large parking space for parking vehicles. The parking scenario becomes worst on special occasions. The conventional developed techniques by installing sensors for parking vehicles become costly. Therefore, a reliable method is required which works for long time to manage the congestion issue. In this thesis, a novel method is proposed for parking vehicles using the metaheuristic approaches. The developed approach provides consistent result using the parameters, parking efficiency and parking space search time. The parking efficiency is improved and parking space searching time reduces from 22.84 to 12.23 seconds using Firefly Algorithm (FA) and feed forward back propagation Neural Network (NN) approach. There should be some mechanism to park the vehicles appropriately; therefore, this research has introduced an enhanced vehicle parking mechanism with the concept of Artificial Intelligence (AI) which helps to get rid of the chaos usually faced. newline