International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Hybridization of Meta-heuristics for Optimizing Routing protocol in VANETsIJERA Editor
The goal of VANET is to establish a vehicular communication system which is reliable and fast which caters to
road safety and road safety. In VANET where network fragmentation is frequent with no central control, routing
becomes a challenging task. Planning an optimal routing plan for tuning parameter configuration of routing
protocol for setting up VANET is very crucial. This is done by defining an optimization problem where
hybridization of meta-heuristics is defined. The paper contributes the idea of combining meta-heuristic
algorithm to enhance the performance of individual search method for optimization problem.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...ijfls
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...Wireilla
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is
the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of
the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted
based on the robot's distance from obstacles, and the target position relative to the instantaneous
orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also,
Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy
systems are determined based on the estimation of the localization process, the information of the obstacles
center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile
robot are determined by the desired fuzzy structures which are applied to its kinematic model.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
Improving Posture Accuracy of Non-Holonomic Mobile Robot System with Variable...TELKOMNIKA JOURNAL
This paper presents a method to decrease imprecision and inaccuracy that have the tendency to
influence the posture of non-holonomic mobile robot by using the adaptive tuning of universe of discourse.
As such, the primary objective of the study is to force the posture error of , , and towards
zero. Hence, for each step of tuning the fuzzy domain, about 20% of imprecision and inaccuracy had been
added automatically into the variable universe fuzzy, while the control input was bound via scaling gain.
Furthermore, the simulation results showed that the tuning of universe fuzzy parameters could increase
the performance of the system from the aspects of response time and error for steady state through better
control of inaccuracy. Besides, the domains of universe fuzzy input [-4,4] and output [0,6] exhibited good
performance in inching towards zero values as the steady state error was about 1% for x(t) position, 0.02%
for y(t) position, and 0.16% for θ(t) orientation, whereas the posture error in the given reference was about
0.0002% .
keywords; Data flow analysis, control dependency .
Program analysis is the method of computing properties of a program.It is useful for performing program optimiztion
Efficient Forecasting of Exchange rates with Recurrent FLANNIOSR Journals
The document proposes a Functional Link Artificial Recurrent Neural Network (FLARNN) model for forecasting foreign exchange rates between currencies like the US dollar, Indian rupee, British pound, and Japanese yen. It compares the performance of the FLARNN model to existing neural network models like LMS and FLANN. The FLARNN uses functional expansion and recurrent connections to more accurately predict exchange rates up to 60 days in the future based on historical data. Experimental results show the FLARNN model consistently outperforms the other methods according to error convergence and Mean Average Percentage Error.
Hybridization of Meta-heuristics for Optimizing Routing protocol in VANETsIJERA Editor
The goal of VANET is to establish a vehicular communication system which is reliable and fast which caters to
road safety and road safety. In VANET where network fragmentation is frequent with no central control, routing
becomes a challenging task. Planning an optimal routing plan for tuning parameter configuration of routing
protocol for setting up VANET is very crucial. This is done by defining an optimization problem where
hybridization of meta-heuristics is defined. The paper contributes the idea of combining meta-heuristic
algorithm to enhance the performance of individual search method for optimization problem.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...ijfls
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...Wireilla
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is
the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of
the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted
based on the robot's distance from obstacles, and the target position relative to the instantaneous
orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also,
Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy
systems are determined based on the estimation of the localization process, the information of the obstacles
center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile
robot are determined by the desired fuzzy structures which are applied to its kinematic model.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
Improving Posture Accuracy of Non-Holonomic Mobile Robot System with Variable...TELKOMNIKA JOURNAL
This paper presents a method to decrease imprecision and inaccuracy that have the tendency to
influence the posture of non-holonomic mobile robot by using the adaptive tuning of universe of discourse.
As such, the primary objective of the study is to force the posture error of , , and towards
zero. Hence, for each step of tuning the fuzzy domain, about 20% of imprecision and inaccuracy had been
added automatically into the variable universe fuzzy, while the control input was bound via scaling gain.
Furthermore, the simulation results showed that the tuning of universe fuzzy parameters could increase
the performance of the system from the aspects of response time and error for steady state through better
control of inaccuracy. Besides, the domains of universe fuzzy input [-4,4] and output [0,6] exhibited good
performance in inching towards zero values as the steady state error was about 1% for x(t) position, 0.02%
for y(t) position, and 0.16% for θ(t) orientation, whereas the posture error in the given reference was about
0.0002% .
keywords; Data flow analysis, control dependency .
Program analysis is the method of computing properties of a program.It is useful for performing program optimiztion
Efficient Forecasting of Exchange rates with Recurrent FLANNIOSR Journals
The document proposes a Functional Link Artificial Recurrent Neural Network (FLARNN) model for forecasting foreign exchange rates between currencies like the US dollar, Indian rupee, British pound, and Japanese yen. It compares the performance of the FLARNN model to existing neural network models like LMS and FLANN. The FLARNN uses functional expansion and recurrent connections to more accurately predict exchange rates up to 60 days in the future based on historical data. Experimental results show the FLARNN model consistently outperforms the other methods according to error convergence and Mean Average Percentage Error.
10 Insightful Quotes On Designing A Better Customer ExperienceYuan Wang
In an ever-changing landscape of one digital disruption after another, companies and organisations are looking for new ways to understand their target markets and engage them better. Increasingly they invest in user experience (UX) and customer experience design (CX) capabilities by working with a specialist UX agency or developing their own UX lab. Some UX practitioners are touting leaner and faster ways of developing customer-centric products and services, via methodologies such as guerilla research, rapid prototyping and Agile UX. Others seek innovation and fulfilment by spending more time in research, being more inclusive, and designing for social goods.
Experience is more than just an interface. It is a relationship, as well as a series of touch points between your brand and your customer. Here are our top 10 highlights and takeaways from the recent UX Australia conference to help you transform your customer experience design.
For full article, continue reading at https://yump.com.au/10-ways-supercharge-customer-experience-design/
How to Build a Dynamic Social Media PlanPost Planner
Stop guessing and wasting your time on networks and strategies that don’t work!
Join Rebekah Radice and Katie Lance to learn how to optimize your social networks, the best kept secrets for hot content, top time management tools, and much more!
Watch the replay here: bit.ly/socialmedia-plan
http://inarocket.com
Learn BEM fundamentals as fast as possible. What is BEM (Block, element, modifier), BEM syntax, how it works with a real example, etc.
The document discusses how personalization and dynamic content are becoming increasingly important on websites. It notes that 52% of marketers see content personalization as critical and 75% of consumers like it when brands personalize their content. However, personalization can create issues for search engine optimization as dynamic URLs and content are more difficult for search engines to index than static pages. The document provides tips for SEOs to help address these personalization and SEO challenges, such as using static URLs when possible and submitting accurate sitemaps.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
This document summarizes a study of CEO succession events among the largest 100 U.S. corporations between 2005-2015. The study analyzed executives who were passed over for the CEO role ("succession losers") and their subsequent careers. It found that 74% of passed over executives left their companies, with 30% eventually becoming CEOs elsewhere. However, companies led by succession losers saw average stock price declines of 13% over 3 years, compared to gains for companies whose CEO selections remained unchanged. The findings suggest that boards generally identify the most qualified CEO candidates, though differences between internal and external hires complicate comparisons.
Fuzzy Logic Model for Traffic CongestionIOSR Journals
Abstract: Traffic congestion has become a serious problem in the urban districts. This is mainly due to the
rapid increase in the number and the use of vehicles. Travel time, travel safety, environmental quality, and life
quality are all adversely affected by traffic congestion. Many traffic control systems have been developed and
installed to alleviate the problem with limited success. Traffic demands are still high and increasing. The main
focus of this report is to introduce a versatile fuzzy logic traffic flow model capable of making optimal traffic
predictions. This model can be used to evaluate various traffic-light timing plans. More importantly, it provides
a framework for implementing adaptive traffic signal controllers based on fuzzy logic technology. When
implemented it solved the problem of waiting time, travel cost, accident, traffic congestion.
Key words: Traffic Congestion, fuzzy logic, Traffic Density, fuzzy controller, conventional controller.
A Brief review to the intelligent controllerswhich used to control trafficflowjournal ijrtem
Abstract: Nowadays, with the social progress and economic development, the transport is playing a pivotal role in cities. The main problem is the traffic jams due to vehicle congestion phenomena at intersection. To solve this problem an intelligent traffic control system that continuously sensing and monitoring traffic conditions and adjusting the timing of traffic lights according to the actual traffic load must be implemented. At present , a variety of traffic control has been designed using electrical technologies.Traffic load is highly dependent on parameters such as day-time , season weather and unpredictable situationssuch as accidents, special events or construction activities, these parameters will cause delay on the traffic flow. The traffic system in Libya is still controlled by old fashion ( i.e equally time interval signal control)and no intelligent system used to monitor and control the traffic flow. The scope of this paper is to review the main Intelligent controllerswhich used in smart traffic systems. Keywords: Traffic, Intelligent control, Programmable logic, Neural network, Fuzzy logic
This document describes a proposed two-stage traffic light system using fuzzy logic to minimize vehicle delay at intersections. The system has two modules: a traffic urgency decision module that selects the next phase to turn green based on traffic urgency, and an extension time decision module that determines how long to extend the green light phase based on vehicle numbers. Software was developed in MATLAB to simulate this system at an isolated intersection and evaluate its performance using average vehicle delay. The document reviews other related works applying fuzzy logic to traffic light control and adaptive signal systems.
A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Inter...ijtsrd
In this paper, a two stage fuzzy logic system has been proposed to control an isolated intersection adaptively. The aim of this work is to minimize the average waiting time for a different traffic flow rates in real time means. In the first stage, the system consists of two modules named next phase selection module and the green phase extension module. In the second stage the system consists of the decision named module. The study was performed using SUMO traffic simulator. A comparison is made between a fuzzy logic controller and a conventional fixed time controller. As a result, fuzzy logic controller has shown better performance. Taha Mahmood | Muzamil Eltejani Mohammed Ali | Akif Durdu ""A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Intersection Based on Real Data using SUMO Simulator"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23873.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23873/a-two-stage-fuzzy-logic-adaptive-traffic-signal-control-for-an-isolated-intersection-based-on-real-data-using-sumo-simulator/taha-mahmood
Improvement of Traffic Monitoring System by Density and Flow Control For Indi...IJSRD
The growth and scale of vehicles today makes management of traffic a constant problem. The existing traffic control system works based on a timing mechanism, meaning an equal time slot is provided for each junction. This is inefficient for non-uniform flow of vehicles. Hence there is a need for a system which is adaptive in nature. Routes should have an option of being granted more time slots depending on the requirements for the given route. This paper proposes a traffic congestion control system which would be adaptive in nature and provide time slot to each route based on traffic density.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
IRJET-Intellectual 4way Traffic Control System using PLC and SCADAIRJET Journal
This document describes an intelligent 4-way traffic control system that uses a PLC and SCADA. It aims to automatically calculate vehicle densities in each lane and prioritize traffic lights accordingly. Sensors measure traffic density data which is sent to the PLC. The PLC program then controls light durations based on density levels to minimize waiting times. This dynamic system aims to more efficiently direct traffic flow compared to conventional fixed-time control systems.
This document provides an introduction, literature review, and discussion of determining the range of thresholds for fuzzy input in traffic flow modeling. It discusses how fuzzy logic can be used to represent traffic parameters like density, speed, and volume linguistically rather than with precise values. The document explores applications of fuzzy logic in traffic management, advantages and disadvantages, and recommends a multidimensional analysis using data, simulations, and machine learning to establish effective threshold ranges that capture traffic dynamics.
IRJET- Efficient and Secure Communication In Vehicular AD HOC NetworkIRJET Journal
The document discusses efficient and secure communication in vehicular ad hoc networks (VANETs). It proposes a Cluster based reliable routing (CRR) protocol. Vehicles are clustered based on their velocity, and a Cluster Controller (CC) is elected based on transmitter heights and position to manage communication among cluster members. The CRR protocol aims to address the challenging routing issues posed by the highly dynamic topology of VANETs.
Multi-Agent System (MAS) monitoring solutions are designed for a plethora of usage topics. Existing approach mostly used cloned back-end architectures while front-end monitoring interface tends to constitute the real specificity of the solution. These interfaces are recurrently structured around three dimensions: access to informed knowledge, agent’s behavioural rules, and restitution of real-time states of specific system sector. In this paper, we propose prototyping a sector-agnostic MAS platform (Smart-X) which gathers in an integrated and independent platform all the functionalities required to monitor and to govern a wide range of sector specific environments. For illustration and validation purposes, the use of Smart-X is introduced and explained with a smart-mobility case study.
Routing of traffic sensors in intelligent transportation systemeSAT Journals
Abstract As country develops, the application of technology in each and every field increases to fulfill the demand of people. The application of technology in transportation system is called Intelligent Transportation System (ITS) which has more demand in today’s world for traffic management. Vehicular Ad hoc Network (VANET) is one of the technology used in Intelligent Transportation System. In Vehicular Ad hoc Network temporary network is formed within the vehicles or vehicle to traffic infrastructure which has sensors within it for communication. The temporary network establishes and ends after exchanging the required information. This process should happen within fraction of seconds which is more complicated issue in highly mobile vehicles, so routing is a major problem in Vehicular Ad hoc Network. In this work, hybrid two stage heuristic routing protocol which is based on ant colony optimization and particle swarm optimization algorithm is used to make routing more efficient in Vehicular Ad hoc Network. The MATLAB software is used to implement the algorithm. The result shows that two stage heuristic protocol perform better than Ad hoc on Demand Vector (AODV) protocol. Keywords: Intelligent Transportation System, Vehicular Ad Hoc Network (VANET), Ad Hoc on Demand Vector (AODV), Ant Colony optimization (ACO), Particle Swarm Optimization (PSO)
IRJET- Analysis and Prediction of Delay at Signalized Junctions in BangaloreIRJET Journal
This document discusses analyzing and predicting delays at signalized intersections in Bangalore, India using various methods. It conducted traffic surveys at intersections to calculate delays using the Highway Capacity Manual (HCM) method. It then used those results to build a linear regression model to predict delays using only 4 key parameters instead of the 18 required by HCM. It found the predicted delays from the regression model were similar to those from HCM. It also proposes designing a fuzzy logic signal control system to dynamically adjust green times based on real-time traffic conditions like queue length and waiting time to further reduce delays. The goal is to improve traffic flow and level of service at intersections using machine learning techniques.
IRJET - Density based Traffic Management SystemIRJET Journal
This document describes a density based traffic management system that uses infrared sensors to detect vehicle counts on roads and adjusts traffic light timing accordingly. The system aims to reduce traffic congestion and unnecessary wait times that occur with fixed-time traffic lights. Infrared sensors are placed along roads every 5 meters and can detect the presence of vehicles passing by. The detected vehicle distances on each road are used to determine traffic density and allocate longer green light times to more congested roads dynamically. The system is controlled using an Arduino mega microcontroller. It analyzes sensor input to adjust traffic signals based on real-time traffic conditions to improve traffic flow compared to conventional fixed-timing traffic lights.
This document presents a study on developing an artificial intelligence system to manage real-time traffic. The study developed a traffic simulator using Python to model vehicle and traffic light behavior at an intersection. A linear regression model was then used to control the traffic lights dynamically based on current traffic conditions, collected from sensors. Testing showed the AI-based dynamic system improved traffic flow compared to a static traffic light system, allowing more vehicles to pass through the intersection in a given time period. The authors conclude the linear regression model provides better real-time traffic management than existing approaches and suggest further improving it with deep learning techniques.
THRESHOLD RANGE FOR TRAFFIC FLOW PARAMETERS USING FUZZY LOGIC.pdfYMYerima
The document discusses fuzzy logic and its application in determining thresholds for traffic flow parameters. It provides context on fuzzy logic and fuzzy input. It then discusses literature on using fuzzy logic to set thresholds for factors like traffic density, speed, and congestion. The literature emphasizes dynamic adjustment of thresholds based on real-time traffic conditions. The document aims to determine an optimal range of thresholds for traffic flow parameters using fuzzy logic models to handle uncertainty in a way that mimics human reasoning. It reviews recent related studies and discusses challenges and potential future directions for research.
This document presents a comparative study of a proposed fuzzy logic mobility based AODV (FLM-AODV) routing protocol and the traditional AODV protocol in mobile ad hoc networks (MANETs). The FLM-AODV protocol considers node mobility as an additional parameter in the route selection process using a fuzzy logic system, in addition to hop count. Simulation results show that FLM-AODV has improved performance over AODV in terms of higher packet delivery ratio, lower average end-to-end delay, and lower normalized routing load. This is because FLM-AODV selects more stable paths with fewer broken links.
10 Insightful Quotes On Designing A Better Customer ExperienceYuan Wang
In an ever-changing landscape of one digital disruption after another, companies and organisations are looking for new ways to understand their target markets and engage them better. Increasingly they invest in user experience (UX) and customer experience design (CX) capabilities by working with a specialist UX agency or developing their own UX lab. Some UX practitioners are touting leaner and faster ways of developing customer-centric products and services, via methodologies such as guerilla research, rapid prototyping and Agile UX. Others seek innovation and fulfilment by spending more time in research, being more inclusive, and designing for social goods.
Experience is more than just an interface. It is a relationship, as well as a series of touch points between your brand and your customer. Here are our top 10 highlights and takeaways from the recent UX Australia conference to help you transform your customer experience design.
For full article, continue reading at https://yump.com.au/10-ways-supercharge-customer-experience-design/
How to Build a Dynamic Social Media PlanPost Planner
Stop guessing and wasting your time on networks and strategies that don’t work!
Join Rebekah Radice and Katie Lance to learn how to optimize your social networks, the best kept secrets for hot content, top time management tools, and much more!
Watch the replay here: bit.ly/socialmedia-plan
http://inarocket.com
Learn BEM fundamentals as fast as possible. What is BEM (Block, element, modifier), BEM syntax, how it works with a real example, etc.
The document discusses how personalization and dynamic content are becoming increasingly important on websites. It notes that 52% of marketers see content personalization as critical and 75% of consumers like it when brands personalize their content. However, personalization can create issues for search engine optimization as dynamic URLs and content are more difficult for search engines to index than static pages. The document provides tips for SEOs to help address these personalization and SEO challenges, such as using static URLs when possible and submitting accurate sitemaps.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
This document summarizes a study of CEO succession events among the largest 100 U.S. corporations between 2005-2015. The study analyzed executives who were passed over for the CEO role ("succession losers") and their subsequent careers. It found that 74% of passed over executives left their companies, with 30% eventually becoming CEOs elsewhere. However, companies led by succession losers saw average stock price declines of 13% over 3 years, compared to gains for companies whose CEO selections remained unchanged. The findings suggest that boards generally identify the most qualified CEO candidates, though differences between internal and external hires complicate comparisons.
Fuzzy Logic Model for Traffic CongestionIOSR Journals
Abstract: Traffic congestion has become a serious problem in the urban districts. This is mainly due to the
rapid increase in the number and the use of vehicles. Travel time, travel safety, environmental quality, and life
quality are all adversely affected by traffic congestion. Many traffic control systems have been developed and
installed to alleviate the problem with limited success. Traffic demands are still high and increasing. The main
focus of this report is to introduce a versatile fuzzy logic traffic flow model capable of making optimal traffic
predictions. This model can be used to evaluate various traffic-light timing plans. More importantly, it provides
a framework for implementing adaptive traffic signal controllers based on fuzzy logic technology. When
implemented it solved the problem of waiting time, travel cost, accident, traffic congestion.
Key words: Traffic Congestion, fuzzy logic, Traffic Density, fuzzy controller, conventional controller.
A Brief review to the intelligent controllerswhich used to control trafficflowjournal ijrtem
Abstract: Nowadays, with the social progress and economic development, the transport is playing a pivotal role in cities. The main problem is the traffic jams due to vehicle congestion phenomena at intersection. To solve this problem an intelligent traffic control system that continuously sensing and monitoring traffic conditions and adjusting the timing of traffic lights according to the actual traffic load must be implemented. At present , a variety of traffic control has been designed using electrical technologies.Traffic load is highly dependent on parameters such as day-time , season weather and unpredictable situationssuch as accidents, special events or construction activities, these parameters will cause delay on the traffic flow. The traffic system in Libya is still controlled by old fashion ( i.e equally time interval signal control)and no intelligent system used to monitor and control the traffic flow. The scope of this paper is to review the main Intelligent controllerswhich used in smart traffic systems. Keywords: Traffic, Intelligent control, Programmable logic, Neural network, Fuzzy logic
This document describes a proposed two-stage traffic light system using fuzzy logic to minimize vehicle delay at intersections. The system has two modules: a traffic urgency decision module that selects the next phase to turn green based on traffic urgency, and an extension time decision module that determines how long to extend the green light phase based on vehicle numbers. Software was developed in MATLAB to simulate this system at an isolated intersection and evaluate its performance using average vehicle delay. The document reviews other related works applying fuzzy logic to traffic light control and adaptive signal systems.
A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Inter...ijtsrd
In this paper, a two stage fuzzy logic system has been proposed to control an isolated intersection adaptively. The aim of this work is to minimize the average waiting time for a different traffic flow rates in real time means. In the first stage, the system consists of two modules named next phase selection module and the green phase extension module. In the second stage the system consists of the decision named module. The study was performed using SUMO traffic simulator. A comparison is made between a fuzzy logic controller and a conventional fixed time controller. As a result, fuzzy logic controller has shown better performance. Taha Mahmood | Muzamil Eltejani Mohammed Ali | Akif Durdu ""A two Stage Fuzzy Logic Adaptive Traffic Signal Control for an Isolated Intersection Based on Real Data using SUMO Simulator"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23873.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/23873/a-two-stage-fuzzy-logic-adaptive-traffic-signal-control-for-an-isolated-intersection-based-on-real-data-using-sumo-simulator/taha-mahmood
Improvement of Traffic Monitoring System by Density and Flow Control For Indi...IJSRD
The growth and scale of vehicles today makes management of traffic a constant problem. The existing traffic control system works based on a timing mechanism, meaning an equal time slot is provided for each junction. This is inefficient for non-uniform flow of vehicles. Hence there is a need for a system which is adaptive in nature. Routes should have an option of being granted more time slots depending on the requirements for the given route. This paper proposes a traffic congestion control system which would be adaptive in nature and provide time slot to each route based on traffic density.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
IRJET-Intellectual 4way Traffic Control System using PLC and SCADAIRJET Journal
This document describes an intelligent 4-way traffic control system that uses a PLC and SCADA. It aims to automatically calculate vehicle densities in each lane and prioritize traffic lights accordingly. Sensors measure traffic density data which is sent to the PLC. The PLC program then controls light durations based on density levels to minimize waiting times. This dynamic system aims to more efficiently direct traffic flow compared to conventional fixed-time control systems.
This document provides an introduction, literature review, and discussion of determining the range of thresholds for fuzzy input in traffic flow modeling. It discusses how fuzzy logic can be used to represent traffic parameters like density, speed, and volume linguistically rather than with precise values. The document explores applications of fuzzy logic in traffic management, advantages and disadvantages, and recommends a multidimensional analysis using data, simulations, and machine learning to establish effective threshold ranges that capture traffic dynamics.
IRJET- Efficient and Secure Communication In Vehicular AD HOC NetworkIRJET Journal
The document discusses efficient and secure communication in vehicular ad hoc networks (VANETs). It proposes a Cluster based reliable routing (CRR) protocol. Vehicles are clustered based on their velocity, and a Cluster Controller (CC) is elected based on transmitter heights and position to manage communication among cluster members. The CRR protocol aims to address the challenging routing issues posed by the highly dynamic topology of VANETs.
Multi-Agent System (MAS) monitoring solutions are designed for a plethora of usage topics. Existing approach mostly used cloned back-end architectures while front-end monitoring interface tends to constitute the real specificity of the solution. These interfaces are recurrently structured around three dimensions: access to informed knowledge, agent’s behavioural rules, and restitution of real-time states of specific system sector. In this paper, we propose prototyping a sector-agnostic MAS platform (Smart-X) which gathers in an integrated and independent platform all the functionalities required to monitor and to govern a wide range of sector specific environments. For illustration and validation purposes, the use of Smart-X is introduced and explained with a smart-mobility case study.
Routing of traffic sensors in intelligent transportation systemeSAT Journals
Abstract As country develops, the application of technology in each and every field increases to fulfill the demand of people. The application of technology in transportation system is called Intelligent Transportation System (ITS) which has more demand in today’s world for traffic management. Vehicular Ad hoc Network (VANET) is one of the technology used in Intelligent Transportation System. In Vehicular Ad hoc Network temporary network is formed within the vehicles or vehicle to traffic infrastructure which has sensors within it for communication. The temporary network establishes and ends after exchanging the required information. This process should happen within fraction of seconds which is more complicated issue in highly mobile vehicles, so routing is a major problem in Vehicular Ad hoc Network. In this work, hybrid two stage heuristic routing protocol which is based on ant colony optimization and particle swarm optimization algorithm is used to make routing more efficient in Vehicular Ad hoc Network. The MATLAB software is used to implement the algorithm. The result shows that two stage heuristic protocol perform better than Ad hoc on Demand Vector (AODV) protocol. Keywords: Intelligent Transportation System, Vehicular Ad Hoc Network (VANET), Ad Hoc on Demand Vector (AODV), Ant Colony optimization (ACO), Particle Swarm Optimization (PSO)
IRJET- Analysis and Prediction of Delay at Signalized Junctions in BangaloreIRJET Journal
This document discusses analyzing and predicting delays at signalized intersections in Bangalore, India using various methods. It conducted traffic surveys at intersections to calculate delays using the Highway Capacity Manual (HCM) method. It then used those results to build a linear regression model to predict delays using only 4 key parameters instead of the 18 required by HCM. It found the predicted delays from the regression model were similar to those from HCM. It also proposes designing a fuzzy logic signal control system to dynamically adjust green times based on real-time traffic conditions like queue length and waiting time to further reduce delays. The goal is to improve traffic flow and level of service at intersections using machine learning techniques.
IRJET - Density based Traffic Management SystemIRJET Journal
This document describes a density based traffic management system that uses infrared sensors to detect vehicle counts on roads and adjusts traffic light timing accordingly. The system aims to reduce traffic congestion and unnecessary wait times that occur with fixed-time traffic lights. Infrared sensors are placed along roads every 5 meters and can detect the presence of vehicles passing by. The detected vehicle distances on each road are used to determine traffic density and allocate longer green light times to more congested roads dynamically. The system is controlled using an Arduino mega microcontroller. It analyzes sensor input to adjust traffic signals based on real-time traffic conditions to improve traffic flow compared to conventional fixed-timing traffic lights.
This document presents a study on developing an artificial intelligence system to manage real-time traffic. The study developed a traffic simulator using Python to model vehicle and traffic light behavior at an intersection. A linear regression model was then used to control the traffic lights dynamically based on current traffic conditions, collected from sensors. Testing showed the AI-based dynamic system improved traffic flow compared to a static traffic light system, allowing more vehicles to pass through the intersection in a given time period. The authors conclude the linear regression model provides better real-time traffic management than existing approaches and suggest further improving it with deep learning techniques.
THRESHOLD RANGE FOR TRAFFIC FLOW PARAMETERS USING FUZZY LOGIC.pdfYMYerima
The document discusses fuzzy logic and its application in determining thresholds for traffic flow parameters. It provides context on fuzzy logic and fuzzy input. It then discusses literature on using fuzzy logic to set thresholds for factors like traffic density, speed, and congestion. The literature emphasizes dynamic adjustment of thresholds based on real-time traffic conditions. The document aims to determine an optimal range of thresholds for traffic flow parameters using fuzzy logic models to handle uncertainty in a way that mimics human reasoning. It reviews recent related studies and discusses challenges and potential future directions for research.
This document presents a comparative study of a proposed fuzzy logic mobility based AODV (FLM-AODV) routing protocol and the traditional AODV protocol in mobile ad hoc networks (MANETs). The FLM-AODV protocol considers node mobility as an additional parameter in the route selection process using a fuzzy logic system, in addition to hop count. Simulation results show that FLM-AODV has improved performance over AODV in terms of higher packet delivery ratio, lower average end-to-end delay, and lower normalized routing load. This is because FLM-AODV selects more stable paths with fewer broken links.
Improving traffic and emergency vehicle clearance at congested intersections ...IJECEIAES
Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Simulation Based Analysis of Bee Swarm Inspired Hybrid Routing Protocol Param...Editor IJCATR
Vehicular Ad-hoc Networks (VANET's) are basically emanated from Mobile Ad hoc networks (MANET's) in which
vehicles act as the mobile nodes, the nodes are vehicles on the road and mobility of these vehicles are very high. The main objective of
VANET is to enhance the safety and amenity of road users. It provides intelligent transportation services in vehicles with the
automobile equipment to communicate and co-ordinates with other vehicles in the same network that informs the driver’s about the
road status, unseen obstacles, internet access and other necessary travel service information’s. The evaluation of vehicular ad hoc
networks applications in based on the simulations. A Realistic Mobility model is a basic component for VANET simulation that
ensures that conclusion drawn from simulation experiments will carry through to real deployments. This paper attempts to evaluate the
performance of a Bee swarm inspired Hybrid routing protocol for vehicular ad hoc network, that protocol should be tested under a
realistic condition including, representative data traffic models, and the realistic movement of the mobile nodes which are the vehicles.
In VANET the simulation of Realistic mobility model has been generated using SUMO and MOVE software and network simulation
has been performed using NS2 simulator, we conducted performance evaluation based on certain metric parameters such as packet
delivery ratio, end-to-end delay and normalized overhead ratio.
IRJET- Intelligent Traffic Signal Control System using ANNIRJET Journal
This document describes a proposed intelligent traffic signal control system that uses image processing and artificial neural networks. Video from cameras at intersections would be used to count vehicles and determine traffic density. The image would first be converted to grayscale and segmented. An artificial neural network would classify segments as vehicles or not. A fuzzy logic controller would then determine appropriate light durations based on vehicle counts to minimize wait times. The system aims to more efficiently control traffic lights than existing fixed-time or sensor-based systems by adapting to real-time traffic conditions.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
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In our second session, we shall learn all about the main features and fundamentals of UiPath Studio that enable us to use the building blocks for any automation project.
📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
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Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
Empowering Transition with Transpiler Support
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Unlocking Creativity with IDE Tools
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Keywords: AI, Containeres, Kubernetes, Cloud Native
Event Link: https://meine.doag.org/events/cloudland/2024/agenda/#agendaId.4211
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...AlexanderRichford
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
"What does it really mean for your system to be available, or how to define w...Fwdays
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
inQuba Webinar Mastering Customer Journey Management with Dr Graham Hill
F046023747
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Design Of Interval Type-Ii Fuzzy Logic Traffic Controller For
Multilane Intersections With Emergency Vehicle Priority System
Using Matlab Simulation
Mohit Jha, Shailja Shukla
Department of Electrical Engineering, Jabalpur Engineering College, Jabalpur, M.P., India
Department of Computer Science Engineering, Jabalpur Engineering College, Jabalpur, M.P., India
Abstract
During the past several years fuzzy logic control has swell from one of the major active and profitable areas for
research in the application of fuzzy set, especially in the zone of industrial process which do not lead themselves
to control conventional methods because of lack of quantitative data regarding the input-output relations. Fuzzy
control is based on fuzzy logic- a logical system which is much closer in spirit to human thinking and natural
language than conventional logical systems. The fuzzy logic controller based on fuzzy logic provides a means of
converting a linguistic control strategy based on expert knowledge into an automatic control strategy. As in
Fuzzy logic traffic controller, the need arises for simulating and optimizing traffic control algorithms to better
accommodate this increasing demand. Fuzzy optimization deals with finding the values of input parameters of a
complex simulated system which result in desired output. This paper presents a MATLAB simulation of fuzzy
logic traffic interval type II controller for controlling flow of traffic in multilane paths. This controller is based
on the waiting time and queue length of vehicles at present green phase and vehicles queue lengths at the other
lanes. The controller controls the traffic light timings and phase difference to ascertain sebaceous flow of traffic
with least waiting time and queue length. In this paper, the multilane model used consists of two alleyways in
each approach. Every outlook has different value of queue length and waiting time, systematically, at the
intersection. The maximum value of waiting time and vehicle queue length has to be selected by using
proximity sensors as inputs to controller for the ameliorate control traffic flow at the intersection. An intelligent
traffic model and fuzzy logic interval type II traffic controller are developed to evaluate the performance of
traffic controller under different pre-defined conditions for oleaginous flow of traffic. Additionally, this fuzzy
logic traffic controller has emergency vehicle siren sensors which detect emergency vehicle movement like
ambulance, fire brigade, Police Van etc. and gives maximum priority to him and pass preferred signal to it.
Keywords-Fuzzy Traffic Controller; Multilane Intersection; Vehicle Actuated Controller; Emergency Vehicle
Selector, Fuzzy Interval type II.
I. INTRODUCTION
Fuzzy logic system (FLS) (also known as a fuzzy
system, fuzzy logic controller, etc) includes fuzzifier,
rules, inference engine, and defuzzyifier. Quite often,
the knowledge that is used to construct the rules in a
FLS is mutable .Today's conventional controllers,
which are developed based on recorded data to
ameliorate timing plans are no longer the fanciful
Solution to traffic intersections due to varying traffic
volumes with respect to time and also increasing
numbers of vehicles on road. Traffic controllers
which will be able to cogitate equal way of human
thinking are designed using Intelligence techniques
like fuzzy logic, neural networks, Genetic Algorithm,
Particle Swarm optimization(PSO), etc. The main
purpose of making new intelligent traffic controllers
is that the traffic controllers that have the overall
efficiency to accommodate to the present time data
from sensors or detectors to perform constant
command of interpreter on the signal timing plan for
multilane intersections in a network in order to reduce
traffic overcrowding which is the main anxiety in
traffic flows control now a day, at multilane traffic
intersections.
Quite often, the knowledge that is used to construct
the rules in a FLS is uncertain. Three ways in which
such rule uncertainty can occur are: 1) the words that
are used in antecedents and consequents of rules can
mean different things to different people ; 2)
consequents obtained by polling a group of experts
will often be different for the same rule because the
experts will not necessarily be in agreement; and 3)
noisy training data. Type-1 FLSs, whose membership
functions are type-1 fuzzy sets, are unable to directly
handle rule uncertainties. Type-2 FLSs, in which
antecedent or consequent membership functions are
type-2 fuzzy sets, can handle rule uncertainties.
General type-2 FLSs is computationally intensive
because type-reduction is very intensive. Things
RESEARCH ARTICLE OPEN ACCESS
2. Mohit Jha Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 6( Version 2), June 2014, pp.37-47
www.ijera.com 38 | P a g e
simplify a lot when secondary membership functions
(MFs) are interval sets (in this case, the secondary
memberships are either zero or one and we call them
interval type-2 sets).
The most commonly used fuzzifier is a singleton;
but, such
a fuzzifier is not adequate when data is corrupted by
measurement noise. In this case, a non-singleton
fuzzifier that treats each measurement as a fuzzy
number should be used. The theory and applications
of a type-1 FLS with non-singleton fuzzifier are
presented in [27], where the input is fuzzified into a
type-1 fuzzy set (e.g., Gaussian) whose parameters
are based on the measured input and the mean and
variance of the measurement noise. This assumes that
the statistical knowledge (mean and variance) of the
noise is given or can be estimated; but, in many cases,
these values are not known ahead of time and cannot
be estimated from the data. Instead, we only have
some linguistic knowledge about the noise, such as
very noisy, moderately noisy, or approximately no
noise.
Human judgment making and Inference in traffic
and carriages are designate by a generally good
execution. Even if the judgment makers have
unfinished information and key judgment merits are
accurately or oracularly as stipulated or not described
at all, and the judgment taking goal are ambiguous,
the capacity of human judgment building is
remarkably. According to [1], traffic intersections
that are managed by human operators are still more
effective as compared to the traffic responsive control
and traditional methods. The older system uses
weight as a trigger mechanism Current traffic systems
react to motion to trigger the light changes [2].
Figure 1 Multilane Traffic Intersection
The first step-in-aid of fuzzy logic controller in
the history in 1977, which displays preferable
execution weigh to vehicle actuated controller for an
exclusively intersection have two one-way roadways
based on a green time extension principle. From this
persuasive work, the main attention for the research
has been initiated on petition for fuzzy control
methods for intersection control greatly focus at a
segregate multilane intersection. Modern traffic
signal controls use highly capable microprocessor
based algorithms to control vehicle movements
through intersections [3]. The utilization of fuzzy
logic controllers in juxtaposition with conventional
pre-timed or vehicle-actuated control modes has
provided improved traffic manipulation ethically to
the usually adopted execution measures as in the case
with delays and number of stops.. Fuzzy controllers
have perfectly demonstrated dominant in controlling
a single traffic intersection, even if the intersection is
in certain complex level. In somewhat illustration,
even if topical controllers perform nice, there is no
clearly warranty that they will continue to do so when
the intersections are concatenate with irregular traffic
flow. Now, further development took place by
accepting fuzzy logic based controllers on traffic
signal for two-way single intersection. In Traffic
signal multilane intersections, vehicle detection
sensors are linked together in order to form an
individual closed network [6].
In this research, extensive description on the
method used in designing the fuzzy logic interval
type II traffic signal controllers and the overall
project development are included. MATLAB is the
exclusive software program used in step-in-aid of the
whole project. The traffic signal controllers are
contemplated using SIMULINK block diagram
provided by MATLAB.
The Interval Type-2 Fuzzy Logic Toolbox
(IT2FLT) is a collection of functions built on the
MATLAB numeric computing environment. It
provides tools for you to create and edit Interval
Type- 2 Fuzzy Inference Systems (IT2FIS) within the
framework of MATLAB.
For fuzzy logic based traffic signal controller
system, Mamdani-Type fuzzy inference system (FIS)
editor is used to develop fuzzy rules, input and output
membership functions. Fuzzy traffic controller will
be constitute either using graphical user interface
(GUI) tools or working from the command line.
Interval type-2 fuzzy sets and fuzzy operators are
the subjects and verbs of interval type-2 fuzzy logic.
These if-then rule statements are used to formulate
the conditional statements that comprise intervaltype-
2 fuzzy logic. A single if-then interval type-2 fuzzy
rule assumes the form
if x is !A then y is !B
Where, !A and !B are linguistic values defined by
interval type-2 fuzzy sets on the ranges (universes of
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ISSN : 2248-9622, Vol. 4, Issue 6( Version 2), June 2014, pp.37-47
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discourse) X and Y, respectively. The if-part of the
rule “x is !A ” is called the antecedent or premise,
while the then-part of the rule “y is !B” is called the
consequent or conclusion. An example of such a rule
might be
In this project, the traffic model is developed
using SIMULINK model block diagram and extended
with the SimEvent block diagram. Nevertheless,
actuated traffic signal controller for multilane
intersection is developed in this project. This fuzzy
logic traffic controller work separately for emergency
vehicles like ambulance, fire-brigade and police van.
They give separate time interval for passing an
emergency vehicle from intersection according to
their movement. The intersection delay time, there
have been a variety of achievements in recent
years [4]. Lastly, the results from the simulations are
shown on waiting time, average delay time and queue
length and presence of emergency vehicle in queue as
execution index for controlling traffic flow at the
intersection.
II. MULTILANE TRAFFIC MODEL
The traffic signal controller for segregate
intersection is shown in Figure 1 is designed based
upon the normal traffic system for eight lane
intersection. The multilane traffic intersection model
developed in MATLAB using Simulink and SimEvent
toolbox is shown in Figure 2.
Figure 2 SIMULINK Block Diagram of Multilane
Traffic Intersection Model
There are four standpoints in this multilane
intersection model with sixteen total movements and a
server traffic light. Each standpoint consists of two
campaigns which are one through campaign and one
right turn campaign. This model is based upon
multiple input single output theory and is constructing
based on three main desired concepts in queuing
theory which are customers, queue, and servers.
There is one more queue model discipline is
applied on all stand points that is first-come-first-out
(FIFO). From queuing theory point of view, the
vehicles are like customers in this model while
services time is the waiting time to get off from
intersection.
Figure 3 SIMULINK Block Diagram of Traffic Proximity
Sensors
Traffic arrival rate and service times of vehicle at
the intersection are independent random variables
with Poisson distribution which means that vehicles
arrival rate at the intersection is Poisson process with
arrival rate λ and the mean of the inter-arrival rate
times between vehicles are 1/λ. The arrival vehicle is
a Poisson process and the numbers of arrival of
vehicles in a system is a Poisson distribution.
Function as shown by Equation 1.
𝑝 𝑞𝑖𝑛 𝑡 = 𝑘 =
(𝜆∆𝑡) 𝑘
𝑒−𝜆∆𝑡
𝑘!
(1)
Where, λ is greater than 0 is the arriving rate
which is equivalent to the number of arrived vehicles
per time period and k=0, 1, 2, ….
III. DESIGN OF FUZZY LOGIC INTERVAL
TYPE II TRAFFIC CONTROLLER
For this project fuzzy logic interval type II traffic
controller is designed using MATLAB Toolbox. The
design has been divided into three stages which are
Green Phase stage, next phase stage, switching stage.
The design structure of fuzzy logic segregate traffic
intersection model controller is shown in Figure 4.
A. Green Phase Stage
The real time traffic conditions of the green phases
are supervised by the Green Phase Stage. Green phase
magnitude value for real time is produced by this
stage according to the present condition observed by
traffic flow using proximity sensors on both side of
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lane. Fuzzy logic controller block and embedded
MATLAB function block that contain C programming
codes are the two main blocks of this stage. This stage
contain "Fuzzy Controller block" which has one set of
Mamdani Type fuzzy inference system which is used
to evaluate green signal extension time on real time. In
this fuzzy controller there is set of 25 rules and fuzzy
inference system this rules takes the value of vehicles
waiting time and the vehicle queue length at real time
at green phase and creates extension time value as an
output. This value is sent to "Embedded MATLAB
function" block for assessment. This block contain if-
else statement which finds the real probability that the
green phase need to extend based on the generated
output from the fuzzy inference system and the queue
length of the other three phases.
Figure 3 SIMULINK Block Diagram of Traffic
Proximity Sensors
Queue length (QL) and waiting time (Wt) are
consumed as the two input variables for fuzzy
inference system in traffic controller using proximity
sensors which is shown in Figure 3. This system
contains input membership function, fuzzy set rules
and output membership function. Here, in both input
and output membership function itritype2 type
membership function is used in place of triangular
membership function because traffic does not change
linearly in real time. The range of vehicle waiting time
is assumed to be 50seconds which is divided into five
different ranges: very short (VS), short (S), long (L),
very long (VL), and extremely long (EL).
Each range coincides to a membership function.
Also there are five ranges of membership functions in
vehicle waiting time (Wt). All of these have standard
deviation (𝜎) of 2 and the constant for itritype2
membership function of very short (VS), short (S),
long (L), very long (VL), and extremely long (EL) are
of 0seconds, 10 seconds, 20 seconds, 30 seconds, and
40 seconds, respectively.
Similarly, for the vehicle queue length (QL), the
range is assumed to be 0 to 50 vehicles in a lane on
each approach at the intersection. The input to a
vehicle queue length (QL) membership function is
very short (VS), short (S), long (L), very long (VL),
and extremely long (EL). All of these have standard
deviation (𝜎) of 2 and the constant for Gaussian
membership function of very short (VS), short (S),
long (L), very long (VL), and extremely long (EL) are
of 0vehicles, 10 vehicles, 20 vehicles, 30 vehicles, and
40 vehicles, respectively.
The output fuzzy variable span which means
extended time of green signal light is divided into 5
ranges analogous to fuzzy sets: zero (Z), short (S),
long (L), very long (VL), and extremely long (EL).
All these membership functions are Gaussian type
with standard deviation (𝜎) of 2 and constant, c which
is equals to 2.5.Fuzzy logic controller is designed with
rule base using IF-THEN conditions. Mainly, fuzzy
rules system is developed with IF-AND-THEN
statements. The fuzzy logic rule base traffic signal
controller at segregate intersection is defined is
TABLE 1. Here, used Interval Type-2 Fuzzy
inference is the process of formulating the mapping
from a given input to an output using interval type-2
fuzzy logic [4]. The mapping then provides a basis
from which decisions can be made, or patterns
discerned
There are two types of fuzzy inference systems
that can be implemented in the Interval Type-2 Fuzzy
Logic Toolbox: Mamdani-type [4, 6, 9] and Sugeno-
type [4, 5, 7]. These two types of inference systems
vary somewhat in the way outputs are determined.
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Interval Type-2 Fuzzy inference systems have
been successfully applied in fields such as automatic
control, data classification, decision analysis, expert
systems, and computer vision [4]. Because of its
multidisciplinary nature, interval type-2 fuzzy
inference systems are associated with a number of
names, such as interval type-2 fuzzy-rule-based
systems, interval type-2 fuzzy expert systems,
interval type-2 fuzzy modeling, interval type-2 fuzzy
associative memory, interval type-2 fuzzy logic
controllers, and simply (and ambiguously) interval
type-2 fuzzy systems.
Mamdani-type interval type-2 fuzzy inference, as
we have defined it for the Interval Type-2 Fuzzy
Logic Toolbox [1-3], expects the output interval type-
2 membership functions to be interval type-2 fuzzy
sets. After the aggregation process, there is a interval
type-2 fuzzy set for each output variable that needs
type-reduction and defuzzification. it is possible, and
in many cases much more efficient, to use a single
spike as the output interval type-2 membership
function rather than a distributed interval type-2
fuzzy set. This is sometimes known as a singleton
output interval type-2 membership function, and it
can be thought of as a pre-type reduction and
defuzzified interval type-2 fuzzy set. It enhances the
efficiency of the type-reduction and defuzzification
process because it greatly simplifies the computation
required by the more general Mamdani method,
which finds the centroid of a two dimensional
functions. Rather than integrating across the two-
dimensional function to find the centroid, we use the
weighted average of a few data points. Sugeno-type
systems support this type of model. In general,
Sugeno-type systems can be used to model any
interval type-2 inference system in which the output
interval type-2 membership functions are either linear
or constant.
Information flows from left to right, from two
inputs to a single output. The parallel nature of the
rules is one of the more important aspects of interval
type-2 fuzzy logic systems. Instead of sharp
switching between modes based on breakpoints, we
will glide smoothly from regions where the system’s
behavior is dominated by either one rule or another.
In the Interval Type-2 Fuzzy Logic Toolbox,
there are five parts of the interval type-2 fuzzy
inference process: fuzzification of the input variables,
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application of the interval type-2 fuzzy operator
(AND or OR) in the antecedent, implication from the
antecedent to the consequent, aggregation of the
consequents across the rules, type-reduction and
defuzzification
The implementation of the IT2FLT GUI is
analogous to the GUI used for Type-1 FLS in the
Matlab Fuzzy Logic Toolbox, thus permitting the
experienced user to adapt easily to the use of IT2FLT
GUI. The Mamdani and Takagi-Sugeno-Kang (TSK)
Interval Type-2 Fuzzy Inference Models and the
design of Interval Type-2 membership functions and
operators are implemented in the IT2FLT reused
from the Matlab commercial Fuzzy Logic Toolbox.
B. Next Phase Stage
This stage controls the phase order based on the
length of vehicle's queue and their extension time of
green light from Green Phase Stage. The SIMULINK
block diagram of next phase stage is shown in Figure
4. This stage pick one phase for the green signal and it
extend the green time of the green phase on the basis
of real time traffic condition of the other three phases.
TABLE I. FUZZY LOGIC RULE BASE FOR TRAFFIC CONTROLLER
Rules
Waiting
Time (Wt)
Queue
Length (QL)
Output
1. VS VS Z
2. VS S Z
3. VS L S
4. VS VL S
5. VS EL L
6. S VS Z
7. S S S
8. S L S
9. S VL L
10. S EL L
11. L VS S
12. L S S
13. L L L
14. L VL L
15. L EL L
16. VL VS S
17. VL S S
18. VL L L
19. VL VL VL
20 VL EL EL
21. EL VS L
22. EL S L
23. EL L L
24. EL VL VL
25. EL EL EL
There are four phases in this stage which are
Green light on East direction is phase1, Green light on
West direction phase2, Green light on South direction
phase3, and Green light on North direction phase4.
The real time series is controlled by the triggered
system. Two output of Next phase stage is connected
by switching stage.
C. Switching Stage
This stage switches current phase to the demanded
next phase by output of their previous stage. If any
other way has more vehicle queue length than current
phase to the next phase basis of output of next phase
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stage. If the present output of any other phase has
more queue length than the queue length of current
green signal phase. Then the next phase stage give
signal to switching stage to change phase to longer
queue. Code for the switching stage is shown in
Figure 4.
Figure 4 SIMULINK Block Diagram of Light Controller Showing All Three Stages Green Phase, Next Phase And Switching Stage.
D. Emergency Vehicle Controlling
All the other blocks of the traffic controller is
same for the emergency vehicle control system
except that an "embedded MATLAB function block"
which passes an emergency vehicle queue length and
their waiting time to it. This function block has C
coding which continuously check for any emergency
vehicle siren noise signal and will active only of a
particular instant of run time and give maximum
priority to emergency vehicle and then after passing
emergency vehicle it revert back to their previous
stage of real time traffic.
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Figure 5(C) Traffic Arrival Process in Lane3
Figure 5(D) Traffic Arrival Process in Lane4
Figure 5(E) Traffic Arrival Process in Lane5
Figure 5(F) Traffic Arrival Process in Lane6
Figure 5(G) Traffic Arrival Process in Lane7
Figure 5(H) Traffic Arrival Process in Lane8
IV. CONCLUSIONS
In this paper, the traffic model and traffic
controller are develop using MATLAB software. This
paper is based on queuing theory model of multiple–
input-single-output. The traffic model is simple to
construct using SIMULINK model and SimEvent
toolbox and IT2FUZZY toolbox in MATLAB. The
traffic controller is developed using fuzzy inference
system method in MATLAB.
To test the effectiveness of this controller here
eight lane different recorded data is considered shown
in Figure 5(A), 5(B), 5(C), 5(D), 5(E), 5(F), 5(G) and
5(H). Also, use certain emergency vehicle data and
test over run time and check the output graph both for
real traffic case and an emergency vehicle case.
Simulation results of green phase switching
shown in Figure 6(A), 6(B), 6(C), 6(D), 6(E), 6(F),
6(G) and 6(H) proves that fuzzy logic interval type 2
traffic controller is superior interval type 1 traffic
controller or to any classical or timing control
methods. In fuzzy logic interval type 1 their
membership functions pass whole values which they
cover in it but in case of interval type 2 they average
passing priority out of all eight lanes and give passing
signal to maximum one. Fuzzy control system
scheme avoids the vehicles waiting in crossing as
much as possible, mitigates the traffic congestion
effectively, improves the intersection vehicle crossing
capacity, efficiency and realizes the intelligent
control of traffic lights. This system is also works
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