An Improved Non-Linear Fuzzy Comprehensive Method for Assessing Urban Freeway Network Traffic Congestion Level

2020 ◽  
Vol 09 (02) ◽  
pp. 68-78
Author(s):  
春肖 董
Keyword(s):  
Network Traffic ◽  
Traffic Congestion ◽  
Comprehensive Method ◽  
Non Linear ◽  
Urban Freeway

IMPROVED EFFICIENT ROUTING STRATEGY ON SCALE-FREE NETWORKS

2012 ◽  
Vol 23 (02) ◽  
pp. 1250016 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG
Keyword(s):  
Network Traffic ◽  
Traffic Congestion ◽  
Heavy Traffic ◽  
Traffic Load ◽  
Transport Efficiency ◽  
Scale Free ◽  
Network Transport ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Path Cost

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási–Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

scholarly journals Comparative Analysis of Traffic Congestion Prediction Models for Cellular Mobile Macrocells

2018 ◽  
Vol 3 (6) ◽  
pp. 32 ◽  
Author(s):  
Aliyu Ozovehe ◽  
Okpo U. Okereke ◽  
Anene E. Chibuzo ◽  
Abraham U. Usman
Keyword(s):  
Neural Network ◽  
Traffic Congestion ◽  
Fuzzy Inference ◽  
Group Method ◽  
Fuzzy Inference Systems ◽  
Great Ability ◽  
Neuro Fuzzy ◽  
Congestion Prediction ◽  
Non Linear ◽  
Inference Systems

Traffic congestion prediction is a non-linear process that involves obtaining valuable information from a set of traffic data and regression or auto-regression linear models cannot be applied as they are limited in their ability to deal with such problems. However, Artificial Intelligent (AI) techniques have shown great ability to deal with non-linear problems and two of such techniques which have found application in traffic prediction are the Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). In this work, Multiple Layer Perceptron Neural Network (MLP-NN), Radial Basis Function Neural Network (RBF-NN), Group Method of Data Handling (GMDH) and an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are trained based on busy hour (BH) traffic measurement data taken from some GSM/GPRS sites in Abuja, Nigeria. The trained networks were then used to predict traffic congestion for some macrocells and their accuracy are compared using four statistical indices. The GMDH model on the average gave goodness of fit (R2), root mean square error (RMSE), standard deviation (σ), and mean absolute error (µ) values of 99, 3.16, 3.53 and 2.32 % respectively. It was observed that GMDH model has the best fit in all cases and on the average predict better than ANFIS, MLP and RBF models. The GMDH model is found to offer improved prediction results in terms of increasing the R2 by 20% and reducing RMSE by 60% over ANFIS, the closest model to the GMDH in term of prediction accuracy.

Virtually Zero Delay Interaction Between Online Game Players Using Kalman Filter-Based Dead Reckoning with Density and Distance Gain Control Adaptation

2019 ◽  
Vol 29 (08) ◽  
pp. 1091-1101
Author(s):  
Jung-Yoon Kim ◽  
Seong-Whan Kim
Keyword(s):  
Kalman Filter ◽  
Network Traffic ◽  
Traffic Congestion ◽  
Prediction Accuracy ◽  
Estimation Error ◽  
Dead Reckoning ◽  
Gain Control ◽  
Estimation Accuracy ◽  
Game Engine ◽  
Network Game

Online 3D games require fast and efficient user interaction support over the network environments, and the networking support is usually implemented by the use of a network game engine. The network game engine should minimize the network delay and mitigate the network traffic congestion. To minimize the network traffic between game users, a client-based prediction (dead reckoning (DR) algorithm) is used. Each game entity uses the algorithm to estimate its own movement as well as the others’. In case the estimation error exceeds the threshold, the entity sends an UPDATE packet which includes velocity, position and the like to other entities. As the estimation accuracy is increased, each entity can minimize the transmission of the UPDATE packet. In this paper, a Kalman filter-based approach is proposed in order to improve the prediction accuracy and an adaptive Kalman gain control in order to minimize the number of UPDATE packets to distant devices. The BZFlag game was used in the experiment in order to verify the proposed approach and the results have shown that it is possible to increase prediction accuracy and reduce the network traffic by 12%.

scholarly journals The Management of Urban Freeway Traffic

1974 ◽  
Vol 1 (2) ◽  
pp. 141-149 ◽  
Author(s):  
Allen R. Cook
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Control Strategies ◽  
False Alarms ◽  
Freeway Traffic ◽  
Detection Algorithms ◽  
Urban Freeway ◽  
And Control ◽  
Alternate Routes

The advent of computer-controlled electronic freeway surveillance and control systems in the past decade represents a potentially significant new operational tool for traffic engineers in large urban areas. These systems are capable of responding to rapidly changing traffic conditions and in various demonstration projects they have proven useful in maintaining an acceptable level of service for freeway operations, reducing the extent and duration of traffic congestion, minimizing the adverse effects of accidents and other incidents on traffic operations, and reducing accident experience. Surveillance system goals and techniques for achieving these goals are reviewed in this paper with particular emphasis on the problem of managing unexpected capacity-reducing incident situations. Recent research has demonstrated the feasibility of detecting incidents from traffic flow data, which is desirable for surveillance purposes because this information can be used to implement control strategies which attempt in real-time to divert some freeway traffic to alternate routes. Some of the operational problems involved with freeway traffic management are discussed, particularly the generation of false alarms by detection algorithms and driver willingness to be diverted to alternate routes.

scholarly journals Use of non-linear dinamics methods for researching network traffic behaviour of high-speed networks

2014 ◽  
Vol 5 (9(71)) ◽  
pp. 46
Author(s):  
Александр Владимирович Карпухин ◽  
Дмитрий Игоревич Грицив ◽  
Александр Анатольевич Ткаченко
Keyword(s):  
Network Traffic ◽  
High Speed ◽  
High Speed Networks ◽  
Non Linear

SEAMLESS VOIP SERVICE USING CENTRALIZED CODEC ADJUSTMENT: A FRAMEWORK IN WIRELESS NETWORK

2015 ◽  
Vol 77 (18) ◽  
Author(s):  
Rajina R. Mohamed ◽  
Wahidah Hashim ◽  
Marina Md. Din
Keyword(s):  
Network Traffic ◽  
Traffic Congestion ◽  
Voice Quality ◽  
Network Access ◽  
Traffic Conditions ◽  
Delay Sensitive ◽  
The Voice ◽  
Crucial Part ◽  
Seamless Service

The evolution of wireless technology leads VoIP application to be a good preferred choice among mobile users. Customers can having a VoIP service while being mobile regardless of location, terminal, and it is independent of network access. It is believed to be an alternative to the PSTN and its service is expected to be as good as PSTN. In essence, QoS plays a crucial part in order to maintain the seamless service during the VoIP session. As wireless networks are prone to channel error and VoIP application is known to be a delay-sensitive application, network traffic congestion could easily affect the voice quality of VoIP. Therefore, the codec selection within the VoIP application must be improved so that the codec can operate at various bit rates in order to cater for different traffic conditions. In this paper, we explain how centralize codec switching can help user to communicate seamlessly. We use WiFi network traffic as an example scenario. 

scholarly journals Network Traffic Lights with Telemetry and Wireless Connectivity Perimeter

2019 ◽  
Vol 256 ◽  
pp. 05002
Author(s):  
España Víctor ◽  
Chuchon Eddy ◽  
Caytuiro David ◽  
Iván Advincula ◽  
Mario Chauca
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Network Traffic ◽  
Traffic Congestion ◽  
Vehicle Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Creation ◽  
Research Document ◽  
Smart Traffic

The following research document seeks to show an alternative to vehicle control systems using existing technologies to develop a system that is efficient and reliable. The creation and operation of a traffic light network will be presented, which will be located in an area where there is traffic congestion. The following network will reorganize, optimize, and measure the vehicular flow in real time. In some countries, intelligent traffic lights have been implemented, with which they have obtained satisfactory benefits by improving the vehicular flow of the places where these systems are located; for this reason we consider it necessary to use smart traffic lights in our country.

Phoenix and the Fight over the Papago-Inner Loop: Race, Class, and the Making of a Suburban Metropolis, 1969-1979

2017 ◽  
Vol 45 (2) ◽  
pp. 211-229
Author(s):  
Nicholas Di Taranto
Keyword(s):  
Inner City ◽  
Low Income ◽  
Traffic Congestion ◽  
Transportation Policy ◽  
Deep Roots ◽  
Race And Class ◽  
Class Discrimination ◽  
Design Changes ◽  
Negative Impacts ◽  
Urban Freeway

Few postwar cities grew as quickly as Phoenix, as suburban, pro-growth policies created a sprawling metropolitan area, but also problems like acute traffic congestion, which policymakers attempted to solve with an urban freeway. The Papago Freeway revolt highlights that transportation policy, like other aspects of suburbanization, had deep roots in intentional and incidental race and class discrimination at all levels of government and private decisions. Moreover, the debate reveals the changing relationship between the federal government and cities under President Nixon and the incendiary political, social, and cultural forces fracturing metropolitan America. The revolt led to design changes that mitigated some of the negative impacts of the freeway, but the Papago still resulted in inequitable outcomes for minorities and low-income populations in the inner city. Most important, it shows that ignoring historical inequities in policy decisions runs the risk of continuing or, worse, exacerbating them.

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