scholarly journals Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Wei Zhang ◽  
Guozhen Tan ◽  
Nan Ding ◽  
Guangyuan Wang

This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on theMobile Centurydataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231

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).


2014 ◽  
Vol 15 (1) ◽  
pp. 42-52 ◽  
Author(s):  
Mario Collotta ◽  
Mario Denaro ◽  
Gianfranco Scatà ◽  
Antonio Messineo ◽  
Giuseppina Nicolosi

Abstract The dynamic management of traffic light cycles is a really interesting research issue considering modern technologies, which can be used in order to optimise road junctions and then improve living conditions of the roads. Wireless sensor networks represent the most suitable technology, as they are easy to deploy and manage. The data relating to road traffic flows can be detected by the sensor network and then processed through the innovative approach, proposed in this work, in order to determine the right green times at traffic lights. Although wireless sensor networks are characterized by very low consumption devices, the continuous information transmission reduces the life cycle of the whole network. To this end, the proposed architecture provides a technique to power the sensor nodes based on piezoelectric materials, which allow producing potential energy taking advantage of the vibration produced by the passage of vehicles on the road.


2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time


KOMTEKINFO ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 176-185
Author(s):  
Dentik Karyaningsih ◽  
Robby Rizky

Traffic jams are a common sight that can be seen in almost all major cities in Indonesia. One of them is in Rangkasbitung City, Lebak Regency. This happens because the number of vehicles continues to increase. The traffic light control system implemented in Indonesia is a static preset time because the time of each phase is predetermined. This type of control system is still not effective in overcoming traffic congestion, especially at certain peak traffic jams. By using the Mamdani fuzzy logic system, it is possible to implement the human mindset into a system. Some rules can be set out in the fuzzy logic controller. The purpose of this study is to design a traffic light control system using fuzzy inference that regulates traffic based on its density. The data used are observations made at the research site. The conclusion of this study is to explain that the fuzzy mamdani method can solve existing problems in traffic congestion in Rangkasbitung City, Lebak Regency, Banten Province


Author(s):  
Tanvika Garg ◽  
Manisha Bharti

UWSN is a grid of many purposes of self-operating nodes with various applications related to various disciplines such as hydrographic surveys, tactical surveillance, disaster prevention, and bathymetry. The process of transmission and reception of messages by propagating sound in an underwater environment is known as acoustic communication. Transmission of acoustic waves is the only method to communicate underwater, as radio waves get attenuated severely and there is severe scattering in optical transmission. Underwater wireless sensor networks (UWSN) have important applications in the exploration of underwater. UWSNs have various applications like in exploration of the sea, collection of data, monitoring of pollution, surveillance of tactics, prevention of disaster, in applications of ministry and surveying of mines.


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