scholarly journals AN EFFICIENT INTELLIGENT TRAFFIC LIGHT CONTROL AND DEVIATION SYSTEM FOR TRAFFIC CONGESTION AVOIDANCE USING MULTI-AGENT SYSTEM

Transport ◽  
2019 ◽  
Vol 35 (3) ◽  
pp. 327-335 ◽  
Author(s):  
Rajendran Sathiyaraj ◽  
Ayyasamy Bharathi
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Ad Hoc ◽  
Road Traffic ◽  
Smart Cities ◽  
Multi Agent System ◽  
Traffic Light ◽  
Traffic Light Control ◽  
Multi Agent ◽  
Hoc Networks

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.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals Dynamic Traffic Light Control

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Monitoring ◽  
Intelligent Transport System ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Traffic Management System

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).

scholarly journals A New Approach of Smart Mobility for Heavy Goods Vehicles in Casablanca

2021 ◽  
Author(s):  
Mohammed Mouhcine Maaroufi ◽  
Laila Stour ◽  
Ali Agoumi
Keyword(s):  
Environmental Sustainability ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Research Work ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Smart Mobility ◽  
Heavy Goods Vehicles

Managing mobility, both of people and goods, in cities is a thorny issue. The travel needs of urban populations are increasing and put pressure on transport infrastructure. The Moroccan cities are no exception and will struggle, in the short term, to respond to the challenges of the acceleration of the phenomenon of urbanization and the increase in demand for mobility. This will inevitably prevent them from turning into smart cities. The term smart certainly alludes to better use of technologies, but smart mobility is also defined as “a set of coordinated actions intended to improve the efficiency, effectiveness and environmental sustainability of cities” [1]. The term mobility highlights the preponderance of humans over infrastructure and vehicles. Faced with traffic congestion, the solutions currently adopted which consist of fitting out and widening the infrastructures, only encourage more trips and report the problem with more critical consequences. It is true that beyond a certain density of traffic, even Intelligent Transport Systems (ITS) are not useful. The concept of dynamic lane management or Advanced Traffic Management (ATM) opens up new perspectives. Its objective is to manage and optimize road traffic in a variable manner, in space and in time. This article is a summary of the development of a road infrastructure dedicated to Heavy Goods Vehicles (HGV), the first of its kind in Morocco. It aims to avoid the discomfort caused by trucks in the urban road network of the city of Casablanca. This research work is an opportunity to reflect on the introduction of ITS and ATM to ensure optimal use of existing infrastructure before embarking on heavy and irreversible infrastructure projects.

scholarly journals Multi-Agent System for Intelligent Urban Traffic Management Using Wireless Sensor Networks Data

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 208
Author(s):  
Maria Viorela Muntean
Keyword(s):  
Traffic Management ◽  
Nearest Neighbor ◽  
Smart Cities ◽  
City Council ◽  
Urban Traffic ◽  
Multi Agent System ◽  
K Nearest Neighbor ◽  
Agent System ◽  
Traffic Lights ◽  
Multi Agent

Intelligent traffic management is an important issue for smart cities. City councils try to implement the newest techniques and performant technologies in order to avoid traffic congestion, to optimize the use of traffic lights, to efficiently use car parking, etc. To find the best solution to this problem, Birmingham City Council decided to allow open-source predictive traffic forecasting by making the real-time datasets available. This paper proposes a multi-agent system (MAS) approach for intelligent urban traffic management in Birmingham using forecasting and classification techniques. The designed agents have the following tasks: forecast the occupancy rates for traffic flow, road junctions and car parking; classify the faults; control and monitor the entire process. The experimental results show that k-nearest neighbor forecasts with high accuracy rates for the traffic data and decision trees build the most accurate model for classifying the faults for their detection and repair in the shortest possible time. The whole learning process is coordinated by a monitoring agent in order to automate Birmingham city’s traffic management.

Pollution Reduction using Intelligent Warning Messages in VANET

2021 ◽  
pp. 57-67
Author(s):  
Esraa Al-Ezaly, Ahmed Abo-Elfetoh and Sara Elhishi ◽  
Keyword(s):  
Air Pollution ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Packet Transmission ◽  
Transmission Delay ◽  
Traffic Light ◽  
Warning Messages ◽  
Warning Message ◽  
Traffic Light Control ◽  
Hoc Networks

Many conferences all over the world about environmental protection are situated. Air pollution resulted is an urgent issue for all people on the earth. Crowded cars in the intersections in traffic light intersections are one of the causes of air pollution. Also, rapid accelerations and deacceleration in the intersection cause air pollution. They also lead to packet transmission delay. This paper treats these issues using an intelligent warning message which reduces crowded cars, rapid accelerations, and deacceleration. Using vehicular ad hoc networks (VANETs), intelligent warning messages are used. Results show that our system outperforms previous studies such as traffic light control and pre-timed method in transmission delay, CO2 emission which causes air pollution.

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.

scholarly journals Overview of Security Issues in Vehicular Ad-hoc Networks

2011 ◽  
pp. 894-911 ◽  
Author(s):  
José María De Fuentes ◽  
Ana Isabel González-Tablas ◽  
Arturo Ribagorda
Keyword(s):  
Ad Hoc Networks ◽  
Traffic Safety ◽  
Traffic Management ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Road Traffic ◽  
High Mobility ◽  
Security Issues ◽  
Vanet Security ◽  
Hoc Networks

Vehicular ad-hoc networks (VANETs) are a promising communication scenario. Several new applications are envisioned, which will improve traffic management and safety. Nevertheless, those applications have stringent security requirements, as they affect road traffic safety. Moreover, VANETs face several security threats. As VANETs present some unique features (e.g. high mobility of nodes, geographic extension, etc.) traditional security mechanisms are not always suitable. Because of that, a plethora of research contributions have been presented so far. This chapter aims to describe and analyze the most representative VANET security developments.

scholarly journals A STOCHASTIC MOBILE DATA TRAFFIC MODEL FOR VEHICULAR AD HOC NETWORKS

2019 ◽  
Vol 01 (01) ◽  
pp. 55-63 ◽  
Author(s):  
Smys S ◽  
Jennifer S. Raj
Keyword(s):  
Ad Hoc Networks ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Traffic Model ◽  
Delivery Ratio ◽  
Data Traffic ◽  
Mobile Data ◽  
Hoc Networks

Routing and mobile data traffic management is a major performance affecting issue in vehicular Ad Hoc networks (VANET). High-rise structures and such radio obstacles cause trouble in proper reception of signals when position-based routing schemes are used. Other major challenges include constrained mobility and irregular distribution of vehicular nodes. A stochastic mobile data traffic model is presented in this paper. This model offers security, reliability, safety and comfort for driving by overcoming the problems of traffic congestion, interference and jamming. It also addresses the handover (HO) issue that occurs during fast mobility. Along with this, the quality parameters of the system such as throughput, packet delivery ratio and delay are also evaluated.

Collaborative Life-Cycle-Based Botnet Detection in IoT Using Event Entropy

2020 ◽  
Vol 10 (4) ◽  
pp. 19-34
Author(s):  
Abdenacer Nafir ◽  
Smaine Mazouzi ◽  
Salim Chikhi
Keyword(s):  
Life Cycle ◽  
Ad Hoc ◽  
Early Stage ◽  
Wide Area Networks ◽  
Central Control ◽  
Multi Agent System ◽  
Botnet Detection ◽  
Multi Agent ◽  
Iot Devices ◽  
Hoc Networks

This paper introduces a collaborative and distributed method for botnet detection in massive networks such as internet of things (IoT) and wide area networks (WAN). The method is model-based and designed as a multi-agent system where the agents are situated on IoT devices. Every agent analyzes the events' entropies, then exchanges its decision with its neighbors aiming at establishing global decision if a botnet is ongoing to be installed within the network or not. Decisions spread over the network where a consensual dominant decision can emerge. In previous similar works, it was necessary to use some central hosts in order to compute global decisions. So, scalability is compromised, and the solution is not suited for massive networks such as IoT. The proposed approach does not require any central control, which allows it to be used in IoT and ad hoc networks. Furthermore, the botnet is detected at the early stage of its life-cycle. Conducted experiments have shown that the proposed approach is well suited for botnet detection in IoT and WAN.

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