scholarly journals Advanced Traffic Management System using A Fuzzy Logic Controller to Differentiate Parking Vehicle and Moving Vehicle

2020 ◽  
Vol 9 (5) ◽  
pp. 488-494
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Traffic Management ◽  
Management System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Smart Cities ◽  
Traffic Density ◽  
Moving Vehicle ◽  
Traffic Management System

In smart cities, traffic congestion is one of the significant problems for citizens. Traffic management is an essential one for the quick development of populace and urban movement in metropolitan areas, and traffic blockage is often seeming on streets. To handle different issues for managing traffic on the streets and to help experts in inappropriate arrangement, a smart traffic management system with the IoT (Internet of Things) is proposed in this paper. Mechanisms to utilize IR sensors to distinguish traffic density isn't easy as smooth a solo vehicle recognized at the last sensor so that it can suggest traffic density in high in any event, even if there is free space before it. A technique to be proposed to solve the previously mentioned issues efficiently is by utilizing the Internet of things for traffic management systems. This paper aims to propose a Fuzzy controller to deal with traffics in smart cities. Fuzzy induction used to compute exact traffic, which separates the parking vehicle and moving vehicle. There is an issue of separating parking and un-parking vehicles in the existing systems. So, we planned to solve this using fuzzy logic.

scholarly journals An IoT Based Intelligent Traffic Management System and Its Implementation on Cupcarbon for Smart Cities

2021 ◽  
Vol 9 (11) ◽  
pp. 1387-1394
Keyword(s):  
Traffic Management ◽  
Management System ◽  
Smart Cities ◽  
Simulation Environment ◽  
Traffic Light ◽  
Traffic Lights ◽  
Sensory Data ◽  
Test Operation ◽  
Traffic Management System ◽  
Alternate Routes

This paper proposes an internet of things (IoT) based intelligent traffic management system that can aid problematic traffic situations in smart cities by classifying congestions via sensory data, and then controlling traffic lights and creating alternate routes for incoming vehicles to the congested zones in order to relieve or avoid congestions completely. The proposed intelligent traffic management system consists of different subsystems such as Test Operation, Supervisory, Traffic Light, and Pathfinder subsystems. The system is represented by flowcharts with their explanations and its operation with some defined scenarios is validated with the CupCarbon simulation environment.

scholarly journals Intelligent Traffic Management Service Using Fuzzy Logic Controller in High Speed Networks

2019 ◽  
pp. 95-98
Author(s):  
Muppineni Sravanthi
Keyword(s):  
Fuzzy Logic ◽  
Traffic Management ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Core Area ◽  
Management Service ◽  
High Speed Networks ◽  
Simulation Results

Network traffic management is a core area of research that is of great importance in the field of communication. This paper proposes a new scheme for controlling router side traffic in networks by updating source sending rate according to its IQ size. A new fuzzy controller is to be modelled to implement the proposed system. Simulation results and comparisons has verified the effectiveness and showed that our proposed scheme can achieve better performances than the existing protocols.

Dynamic Routing of Emergency Vehicles with Traffic Management System and Implementation on CupCarbon for Smart Cities

2021 ◽  
Vol 9 (11) ◽  
pp. 1407-1412
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Smart Cities ◽  
Maximum Speed ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Management System ◽  
On The Road

The traffic congestion is one of the major problems in crowded cities, which causes people to spend hours on the road. In traffic congestion situations, finding alternate routes for emergency vehicles, which provides shortest travel time to nearby hospital is critically life-saving issue. In this paper, we propose a traffic management system and an algorithm for routing of an emergency vehicle. The algorithm uses distance between source and destination, maximum vehicle count, maximum speed, average speed, traffic light conditions on the roads, which are assumed to support vehicle-to-infrastructure (V2I) communication in 5G IoT network. Simulations are performed on CupCarbon IoT simulator platform for various test scenarios. The performance of the proposed emergency vehicle routing algorithm is compared against well known Link State algorithm. And, the results demonstrate the effectiveness of the proposed method.

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