Modified Fuzzy-Based Smart Barricade Movement for Traffic Management System

In urban areas, the traffic congestion is the major prevalent transportation issue, and the vehicular traffic management is the critical concern for the town planners. As the road network is added day by day, the effort on traffic management is more crucial. So far, more contributions have been made in the traffic management problem, still there lags a gap on attaining accurate result. This paper introduces a new traffic management system with the use of smart barricade system. Basic concept of this smart system is the localization of barricade that is based on nature as well as the intensity of traffic with respect to three barricade modes: open, close, and partially open. To develop the smart barricade system for dynamic traffic management, initially, the historical data collection is done. The collection of historical data is enabled by adopting various traffic centres that facilitate the collection number of vehicles per instant and the vehicles speed. In this model, the placing of barricade is decided by the fuzzy logic system, and the system also concentrates on finding optimal membership limits to attain better results. For this, this paper proposes a new algorithm named Modified Grasshopper Optimization Algorithm with New Position, which is the modification of GOA. Finally, the proposed model compares its performance over other methods like conventional GOA, Particle Swarm Optimization, Firefly, Grey Wolf Optimization with respect to measures like number of vehicle transmitting and vehicle distribution, and proves the betterment of proposed model.