scholarly journals Speedometer reliability in regard to road traffic sustainability

2021 ◽  
Vol 11 (1) ◽  
pp. 1059-1068
Author(s):  
Ján Ondruš ◽  
Marián Gogola ◽  
Kristián Čulík ◽  
Rudolf Kampf ◽  
Ladislav Bartuška
Keyword(s):  
Road Traffic ◽  
Real Data ◽  
Measuring Device ◽  
The Real ◽  
Traffic Conditions ◽  
Traffic Lane ◽  
Road Section ◽  
Speed Change ◽  
Instantaneous Speed

Abstract The speedometer with radar head is a device displaying the instantaneous speed of vehicles in both the directions of the traffic lane. Interactive with the video, it collects and effectively interprets particular statistic data, such as the number of passed vehicles, classification of vehicles, exceeded speed, drivers´ behavior – speed change right before the measuring device, etc. The video is synchronized with the radar. In the areas where speedometer is installed, it is predicted that about 30% of the drivers slow down in front of the measuring device and about 60–90% of vehicles slow down after passing the device. The speedometer also serves as a light decelerator with respect to safe and sustainable traffic. The aim of the research was to carry out and subsequently to evaluate the three profile reviews executed on the selected road section under specific light and traffic conditions. After that, the evaluated data was compared with the real data gained by the respective reviews. The result of such comparison showed the measure of reliability and accuracy of the speedometer.

scholarly journals ANALYSIS OF DRIVER BEHAVIOR IN VEHICLE FOLLOWING AND LANE CHANGING PARAMETERS ON URBAN MID BLOCK SECTIONS

2021 ◽  
Vol 9 (2) ◽  
pp. 1169-1177
Author(s):  
Sowjanya, Et. al.
Keyword(s):  
Road Traffic ◽  
Driver Behavior ◽  
Video Data ◽  
Heterogeneous Traffic ◽  
Heterogeneous Environments ◽  
Trajectory Data ◽  
Lateral Direction ◽  
Lane Changing ◽  
Traffic Conditions ◽  
Road Section

In mixed traffic situations, there is weak or no lane behavior of the driver much more complicated where vehicle and driver behavior show a huge difference between them. Road traffic driving behavior on urban midblock sections is one of the most complex phenomena to be examined particularly in heterogeneous traffic conditions. This is often attributed to the capacity of the road section and the traffic flow features at the macroscopic and microscopic level of a road section. Very few researchers have attempted to investigate these features in heterogeneous environments because of the lack of adequate information gathering methods and the amount of complexity involved. In this background, an access controlled mid block road section was selected for video data collection. The main objectives of this study include developing vehicular trajectory data and analyzing the lane changing and vehicle following behavior of driver on the mid block section considering the relative velocities and relative spacing between various types of vehicles under heterogeneous traffic conditions.  The videos were collected from urban roadway in the Kurnool district of Andhra Pradesh. The length of the stretch is 120m and the width is 7.0 m. The data was extracted to know the variations in terms of longitudinal and lateral speeds, velocities, vehicle following and lane changing behavior of the drivers. The data extracted was smoothened by moving average method to minimize the human errors. Lateral amplitude of the vehicles of various types was analyzed. The study revealed that vehicles in the mixed stream, in general and in particular, Bikes and Autos particularly move substantially in the lateral direction.

Study on Satisfaction Evaluation of Urban Road Traffic Conditions

2013 ◽  
Vol 361-363 ◽  
pp. 2344-2348
Author(s):  
Jing Fei Yu ◽  
Li Dong Wang ◽  
Nan Nan Wang ◽  
Xin Jie Zhang
Keyword(s):  
Road Traffic ◽  
Common Factors ◽  
Weighting Factor ◽  
Actual Situation ◽  
Urban Road ◽  
The Road ◽  
Traffic Conditions ◽  
Road Section ◽  
Four Levels ◽  
Satisfaction Evaluation

From the basic feelings of urban road use, the paper selects 15 indicators to factor analysis for satisfaction of urban road use; those indicators are attributed to the four common factors, final the scores of integrated weighting factor is taken variable to cluster analysis. The results showed that the satisfaction of 13 road sections that was selected can be divides into four levels. By comparison, the results of analysis are more in line with the actual situation of the road section, therefore the results can provide a basis to enhance and improve road conditions for the relevant personnel.

A Versatile Multi-Agent Traffic Simulator Framework Based on Real Data

2016 ◽  
Vol 25 (01) ◽  
pp. 1660006 ◽  
Author(s):  
Alexandre Bonhomme ◽  
Philippe Mathieu ◽  
Sébastien Picault
Keyword(s):  
Decision Support ◽  
Road Traffic ◽  
Real Data ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Traffic Conditions ◽  
Prototype Tool ◽  
Microscopic Models ◽  
Wide Range ◽  
Multi Agent

Among real-system applications of AI, the field of traffic simulation makes use of a wide range of techniques and algorithms. Especially, microscopic models of road traffic have been expanding for several years. Indeed, Multi-Agent Systems provide the capability of modeling the very diversity of individual behaviors. Several professional tools provide comprehensive sets of ready-made, accurate behaviors for several kinds of vehicles. The price in such tools is the difficulty to modify the nature of programmed behaviors, and the specialization in a single purpose, e.g. either studying resulting ows, or providing an immersive virtual reality environment. Thus, we advocate for a more exible approach for the design of multi-purpose tools for decision support. Especially, the use of geographical open databases offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. Our proposal also makes decision support systems able to integrate environmental and behavioral modifications in a linear fashion, and to compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and ows. We also describe here the prototype tool that has been implemented according to our design principles.

scholarly journals The model of recognition of driving styles and classification of traffic interaction strategies

2017 ◽  
Vol 8 (4) ◽  
pp. 123-133 ◽  
Author(s):  
S.B. Efremov
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Road Traffic ◽  
Future Design ◽  
Traffic Conditions ◽  
Dangerous Driving ◽  
The Neural Network

In this paper, we propose the grounds for constructing a neural network model for recognizing the driving styles with the aim of classifying the types interaction strategies of drivers in road traffic. The purpose of this article is that the possible future design of systems for recognizing the driving styles based on the neural network. Our system is able to identify and classify strategies for interaction of drivers in traffic conditions, as well as to allocate traffic interaction strategies that can be correlated with “types of dangerous driving”.

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

Index of suicide risk in Mexico using Twitter

2019 ◽  
pp. 1-13
Author(s):  
Luz Judith Rodríguez-Esparza ◽  
Diana Barraza-Barraza ◽  
Jesús Salazar-Ibarra ◽  
Rafael Gerardo Vargas-Pasaye
Keyword(s):  
Social Networks ◽  
Analytic Hierarchy Process ◽  
Suicide Risk ◽  
Opinion Mining ◽  
Real Data ◽  
Analytic Hierarchy ◽  
Specialized Care ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if they show signs of depression or not. However, they have neglected the quantification of the risk of committing suicide. Therefore, this article proposes a new index for identifying suicide risk in Mexico. Methodology: The proposal index is constructed through opinion mining using Twitter and the Analytic Hierarchy Process. Contribution: Using R statistical package, a study is presented considering real data, making a classification of people according to the obtained index and using information from psychologists. The proposed methodology represents an innovative prevention alternative for suicide.

Single Depth View Based Real-Time Reconstruction of Hand-Object Interactions

2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu
Keyword(s):  
Real Time ◽  
Synthetic Data ◽  
Real Data ◽  
Depth Image ◽  
Real Time System ◽  
The Real ◽  
Time Performance ◽  
Contact Constraint ◽  
Object Shapes ◽  
Object Interactions

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.

scholarly journals A fractional order epidemic model for the simulation of outbreaks of Ebola

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Weiqiu Pan ◽  
Tianzeng Li ◽  
Safdar Ali
Keyword(s):  
Numerical Solution ◽  
Root Mean Square ◽  
Fractional Order ◽  
Relative Error ◽  
Numerical Solutions ◽  
Real Data ◽  
Mean Square ◽  
Order Model ◽  
The Real ◽  
Fractional Orders

AbstractThe Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number $R_{0}$ R 0 , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error $g(U^{*})=0.4146$ g ( U ∗ ) = 0.4146 are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is $g(U^{*})=0.2744$ g ( U ∗ ) = 0.2744 . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data.

Petrophysical Facies Classification Based on Fuzzy Inference Networks

2013 ◽  
Vol 634-638 ◽  
pp. 4017-4021
Author(s):  
Jun Hui Pan ◽  
Hui Wang ◽  
Xiao Gang Yang
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Reasoning ◽  
Real Data ◽  
Analysis Data ◽  
Classification Model ◽  
Core Analysis ◽  
Development Zone ◽  
The Real ◽  
Facies Classification ◽  
Quantitative Indicators

Aiming at the petrophysical facies recognition, a novel identification method based on the weighted fuzzy reasoning networks is proposed in the paper. First, the types and indicators are obtained from core analysis data and the results given by experts, and then the standard patterning database of reservoir petrophysical facies is established. Secondly, by integrating expert experiences and quantitative indicators to reflect the change of petrophysical facies, the classification model of petrophysical facies based on the weighted fuzzy reasoning networks is designed. The preferable application results are presented by processing the real data from the Sabei development zone of Daqing oilfield.

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