An Efficient Intelligent Traffic Light Control and Deviation System for Traffic Congestion Avoidance Using Multi-Agent System

Abstract

<jats:p>An efficient and intelligent road traffic management system is the corner stone for every smart cities. Vehicular Ad-hoc NETworks (VANETs) applies the principles of mobile ad hoc networks in a wireless network for Vehicle-to-vehicle data exchange communication. VANETs supports in providing an efficient Intelligent Transportation System (ITS) for smart cities. Road traffic congestion is a most common problem faced by many of the metropolitan cities all over the world. Traffic on the road networks are widely increasing at a larger rate and the current traffic management systems is unable to tackle this impediment. In this paper, we propose an Efficient Intelligent Traffic Light Control and Deviation (EITLCD) system, which is based on multi-agent system. This proposed system overcomes the difficulties of the existing traffic management systems and avoids the traffic congestion problem compare to the prior scenario. The proposed system is composed of two systems: Traffic Light Controller (TLC) system and Traffic Light Deviation (TLD) system. The TLC system uses three agents to supervise and control the traffic parameters. TLD system deviate the vehicles before entering into congested road. Traffic and travel related information from several sensors are collected through a VANET environment to be processed by the proposed technique. The proposed structure comprises of TLC system and makes use of vehicle measurement, which is feed as input to the TLD system in a wireless network. For route pattern identification, any traditional city map can be converted to planar graph using Euler’s path approach. The proposed system is validated using Nagel–Schreckenberg model and the performance of the proposed system is proved to be better than the existing systems in terms of its time, cost, expense, maintenance and performance.</jats:p>

Integrated tripartite modules for intelligent traffic light system

“…The Nash bargaining algorithm optimizes the traffic signal timings at every signalized intersection. Sathiyaraj et al [21] The proposed Intelligent traffic light management and deviation (EITLCD) system is predicated on a multi-agent system. The planned system consists of two systems: traffic light controller (TLC) system and traffic light deviated (TLD) system.…”

A multi-agent Framework for dynamic traffic management Considering Priority Link

“…The ITS incorporate artificial technologies to overcome the congestion challenges and other transportation issues that are difficult to address using traditional computational techniques. The widely used artificial intelligence techniques for optimizing traffic signals are Artificial Neural network System [3][4], Deep Learning [5][6] [7], Genetic Algorithm [8] [9], Fuzzy logic (FL) [10], Multi-Agent System (MAS) [11], Case-Based Reasoning [12] and Ant Colony Algorithm [13]. These methods are used to handle diverse problems, e.g., traffic congestion [14], incident detection [15], and route guidance [16].…”

Multiagent Model of Rail-Road Intersection with Connected Vehicles

“…Multiagent approach is one of popular modelling approaches applied in complex systems modelling [21][22][23]. In our context the multiagent approach is understood as a supplemental approach to modelling complex systems.…”