Fuzzy Logic System in Quantifying Human Driving Skill for Human Adaptive Mechatronics

2015 ◽  
Vol 735 ◽  
pp. 304-310 ◽  
Author(s):  
Mohamad Hafis Izran Ishak ◽  
A.W.A. Aziz ◽  
M.F.A.M. Kasai
Keyword(s):  
Computer Simulation ◽  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Simulation Software ◽  
Membership Functions ◽  
Human Skill ◽  
Input And Output ◽  
Driving Skill ◽  
Human Skills ◽  
Logic System

Human Adaptive Mechatronic (HAM) is an enhance system for Human Machine System (HMS). Instead of one-way relationship between human and machine, HAM system provides two-way relationship between human and machine in order to assist human and to improve human skills in operating the machine. Driving a car is an example of applications where HAM system can be applied. One of the problems of HAM is to quantify the human skill for operating the machine. Therefore, this paper proposed a method to quantify human driving skill using Fuzzy Logic System (FLS). In order to get the best design of FLS for quantifying human driving skill, twelve designs of FLS were designed and tested using computer simulation software. The best design from all twelve designs is then been compared with other method of quantifying human skill for verification. Results show that the design of membership functions for input and output have big impact to the accuracy of the output.

scholarly journals Investigation of Critical Gap for Pedestrian Crossing Using Fuzzy Logic System

2020 ◽  
Vol 10 (10) ◽  
pp. 3653 ◽  
Author(s):  
Wafaa Shoukry Saleh ◽  
Maha M A Lashin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Transport Infrastructure ◽  
Membership Functions ◽  
Triangular Form ◽  
Critical Gap ◽  
Infrastructure Design ◽  
Input Variables ◽  
Pedestrian Crossing ◽  
Logic System

This paper assesses pedestrian crossing behavior and critical gaps at a two-way midblock crossing location. A critical gap is the shortest gap that a pedestrian accepts when crossing a road. A dataset was collected in 2017 in Edinburgh (UK). The analysis was performed using the fuzzy logic system. The adopted membership function of the fuzzy logic system is of a triangular form since it has a simple and convenient structure. The input variables that are used in the analysis are the number and length of rejected gaps and length of accepted gaps at the crossing location. The output variables are the critical gaps. The results show that assessing critical gap estimation of pedestrians crossing using fuzzy logic is achievable and produces reasonable values that are comparable to values that are reported in the literature. This outcome improves the understanding of pedestrian crossing behavior and could therefore have implications for transport infrastructure design. Further analysis using additional parameters including waiting time and demographic characteristics and alternative forms for membership functions are strongly encouraged.

scholarly journals A Strain-Based Intelligent Tire to Detect Contact Patch Features for Complex Maneuvers

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1750 ◽  
Author(s):  
Mª Fernanda Mendoza-Petit ◽  
Daniel García-Pozuelo ◽  
Vicente Díaz ◽  
Oluremi Olatunbosun
Keyword(s):  
Fuzzy Logic ◽  
Contact Point ◽  
Contact Length ◽  
Fuzzy Logic System ◽  
Simulation Software ◽  
Slip Angle ◽  
Rolling Velocity ◽  
Contact Patch ◽  
Essential Components ◽  
Logic System

Tires are essential components of vehicles and are able to transmit traction and braking forces to the contact patch, contribute to directional stability, and also help to absorb shocks. If these components can provide information related to the tire–road interaction, vehicle safety can be increased. This research is focused on developing the tire as an active sensor capable to provide its functional parameters. Therefore, in this work, we studied strain-based measurements on the contact patch to develop an algorithm to compute the wheel velocity at the contact point, the effective rolling radius and the contact length on dynamic situations. These parameters directly influence the dynamics of wheel behavior which nowadays is not clearly defined. Herein, hypotheses have been assumed based on previous studies to develop the algorithm. The results expose to view an experimental test regarding influence of the tire operational condition (slip angle, vertical load, and rolling velocity) onto the computed parameters. This information is used to feed a fuzzy logic system capable of estimating the effective radius and contact length. Furthermore, a verification process has been carried out using CarSim simulation software to get the inputs for the fuzzy logic system at complex maneuvers.

scholarly journals Use of the Fuzzy-Logic for Control of Accuracy and Increase of Production Quality

2018 ◽  
pp. 52-57
Author(s):  
I. Hrihorenko ◽  
S. Hrihorenko ◽  
E. Bezborodyi
Keyword(s):  
Computer Simulation ◽  
Fuzzy Logic ◽  
User Interface ◽  
Technological Process ◽  
Production Quality ◽  
Fuzzy Logic System ◽  
Factors Influencing ◽  
Definition Of ◽  
Logic System

The paper deals with the solution of the scientific and practical task of controlling the accuracy of the parameters of the process of making kefir and improving its quality by creating a heuristic analyzer based on the user interface of the fuzzy logic system. The factors influencing the accuracy of the operation of the digital meter are analyzed, the possibility of using the fuzzy logic apparatus has been proved to determine the parameters of the technological process that ensure the maximum quality of the product. Computer simulation was carried out, which confirmed that the creation of a heuristic analyzer for determining the quality of yogurt is appropriate and necessary in order to prevent the production of low-quality products through the definition of the stage of production on which there is a deviation of the technology and timely eliminate the violation.

Fuzzy Logic System for Abnormal Audio Event Detection Using Mel Frequency Cepstral Coefficients

2017 ◽  
Vol 21 (2) ◽  
pp. 205-210
Author(s):  
Cristina P. Dadula ◽  
◽  
Elmer P. Dadios
Keyword(s):  
Fuzzy Logic ◽  
Event Detection ◽  
Fuzzy Logic System ◽  
Membership Functions ◽  
Mel Frequency Cepstral Coefficients ◽  
Average Accuracy ◽  
Audio Event ◽  
Cepstral Coefficients ◽  
Range Of Values ◽  
Logic System

This paper presents a fuzzy logic system for audio event detection using mel frequency cepstral coefficients (MFCC). Twelve MFCC of audio samples were analyzed. The range of values of MFCC were obtained including its histogram. These values were normalized so that its minimum and maximum values lie between 0 and 1. Rules were formulated based on the histogram to classify audio samples as normal, gunshot, or crowd panic. Five MFCC were chosen as input to the fuzzy logic system. The membership functions and rules of the fuzzy logic system are defined based on the normalized histograms of MFCC. The system was tested with a total of 150 minutes of normal sounds from different buses and 72 seconds audio clips abnormal sounds. The designed fuzzy logic system was able to classify audio events with an average accuracy of 99.4%.

scholarly journals Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

2021 ◽  
Vol 69 (2) ◽  
pp. 355-390
Author(s):  
Teodora Milošević ◽  
Dragan Pamučar ◽  
Prasenjit Chatterjee
Keyword(s):  
Fuzzy Logic ◽  
Hazardous Materials ◽  
Fuzzy Logic System ◽  
Membership Functions ◽  
Fuzzy Logic Systems ◽  
Input Variables ◽  
Weighting Coefficients ◽  
Consistency Method ◽  
Selection Of ◽  
Logic System

Introduction/purpose: The paper presents a model for the selection of a route for the transport of hazardous materials using fuzzy logic systems, as a type of artificial intelligence systems. The system presented in the paper is a system for assistance in the decisionmaking process of the traffic service authorities when choosing one of several possible routes on a particular path when transporting hazardous materials. Methods: The route evaluation is performed on the basis of five criteria. Each input variable is represented by three membership functions, and the output variable is defined by five membership functions. All rules in a fuzzy logic system are determined by applying the method of weight premise aggregation (ATPP), which allows the formation of a database based on experience and intuition. Based on the number of input variables and the number of their membership functions, the basic base of 243 rules is defined. Three experts from the Ministry of Defense were interviewed to determine the weighting coefficients of the membership functions, and the values of the coefficients were determined using the Full Consistency Method (FUCOM). Results: A user program which enables the practical application of this model has been created for the developed fuzzy logic system. Conclusion: The user platform was developed in the Matlab 2008b software package.

A New Hardware Architecture for Fuzzy Logic System Acceleration

2016 ◽  
Vol 12 (2) ◽  
pp. 188-197
Author(s):  
A yahoo.com ◽  
Aumalhuda Gani Abood aumalhuda ◽  
A comp ◽  
Dr. Mohammed A. Jodha ◽  
Dr. Majid A. Alwan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Hardware Architecture ◽  
Logic System

Penerapan Logika Samar dalam Peramalan Data Runtun Waktu

2011 ◽  
Vol 3 (2) ◽  
pp. 11-15
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Time Series Analysis ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Time Series Data ◽  
Fuzzy Logic System ◽  
Series Data ◽  
Series Analysis ◽  
Logic System

Recently, there are so many soft computing methods been used in time series analysis. One of these methods is fuzzy logic system. In this paper, we will try to implement fuzzy logic system to predict a non-stationary time series data. The data we use here is Mackey-Glass chaotic time series. We also use MATLAB software to predict the time series data, which have been divided into four groups of input-output pairs. These groups then will be used as the input variables of the fuzzy logic system. There are two scenarios been used in this paper, first is by using seven fuzzy sets, and second is by using fifteen fuzzy sets. The result shows that the fuzzy system with fifteen fuzzy sets give a better forecasting result than the fuzzy system with seven fuzzy sets. Index Terms—forecasting, fuzzy logic, Mackey-Glass chaotic, MATLAB, time series analysis

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