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.
Solving real world delivery problem using improved max-min ant system with lo...ijaia
This paper presents a solution to real-world delive
ry problems (RWDPs) for home delivery services wher
e
a large number of roads exist in cities and the tra
ffic on the roads rapidly changes with time. The
methodology for finding the shortest-travel-time to
ur includes a hybrid meta-heuristic that combines a
nt
colony optimization (ACO) with Dijkstra’s algorithm
, a search technique that uses both real-time traff
ic
and predicted traffic, and a way to use a real-worl
d road map and measured traffic in Japan. We
previously proposed a hybrid ACO for RWDPs that use
d a MAX-MIN Ant System (MMAS) and proposed a
method to improve the search rate of MMAS. Since tr
affic on roads changes with time, the search rate i
s
important in RWDPs. In the current work, we combine
the hybrid ACO method with the improved MMAS.
Experimental results using a map of central Tokyo a
nd historical traffic data indicate that the propos
ed
method can find a better solution than conventional
methods.
Optimized Traffic Signal Control System at Traffic Intersections Using VanetIOSR Journals
Abstract: Traditional Automated traffic signal control systems normally schedule the vehicles at intersection in
a pre timed slot manner. This pre-timed controller approach fails to minimize the waiting time of vehicles at the
traffic intersection as it doesn’t consider the arrival time of vehicles. To overcome this problem an adaptive and
intelligent traffic control system is proposed in such a way that a traffic signal controller with wireless radio
installed at the intersection and it is considered as an infrastructure. All the vehicles are equipped with onboard
location, speed sensors and a wireless radio to communicate with the infrastructure thereby VANET is formed.
Once the vehicles enter into the boundary of traffic area, they broadcast their positional information as data
packet with their encapsulated ID in it. The controller at the intersection receives the transmitted packets from
all the legs of intersection and then stores it in a temporary log file. Now the controller runs Platooning
algorithm to group the vehicles approximately in equal size of platoons. The platoons are formed on the basis of
data disseminated by the vehicles. Then the controller runs Oldest Job First algorithm which treats platoons as
jobs. The algorithm schedules jobs in conflict free manner and ensures all the jobs utilize equal processing time
i.e the vehicles of each platoons cross the intersection at equal delays. The proposed approach is evaluated
under various traffic volumes and the performance is analyzed.
Keywords Conflict graphs, online job scheduling, traffic signal control, vehicular ad hoc network (VANET)
simulation, vehicle-actuated traffic signal control, Webster’s algorithm.
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.
Autonomous Traffic Signal Control using Decision Tree IJECEIAES
The objective of this paper is to introduce an effective and efficient way of traffic signal light control to optimize the traffic signal duration across each lanes and thereby, to minimize or completely eliminate traffic congestion. This paper introduces a new approach to resolve the traffic congestion problem at junctions by making use of decision trees. The vehicle count in the real time traffic video is determined by Image Processing technique. This information is fed to the decision tree based on which the decision is made regarding the status of traffic signal lights of each lane at the junction at any given instant of time.
Solving real world delivery problem using improved max-min ant system with lo...ijaia
This paper presents a solution to real-world delive
ry problems (RWDPs) for home delivery services wher
e
a large number of roads exist in cities and the tra
ffic on the roads rapidly changes with time. The
methodology for finding the shortest-travel-time to
ur includes a hybrid meta-heuristic that combines a
nt
colony optimization (ACO) with Dijkstra’s algorithm
, a search technique that uses both real-time traff
ic
and predicted traffic, and a way to use a real-worl
d road map and measured traffic in Japan. We
previously proposed a hybrid ACO for RWDPs that use
d a MAX-MIN Ant System (MMAS) and proposed a
method to improve the search rate of MMAS. Since tr
affic on roads changes with time, the search rate i
s
important in RWDPs. In the current work, we combine
the hybrid ACO method with the improved MMAS.
Experimental results using a map of central Tokyo a
nd historical traffic data indicate that the propos
ed
method can find a better solution than conventional
methods.
Optimized Traffic Signal Control System at Traffic Intersections Using VanetIOSR Journals
Abstract: Traditional Automated traffic signal control systems normally schedule the vehicles at intersection in
a pre timed slot manner. This pre-timed controller approach fails to minimize the waiting time of vehicles at the
traffic intersection as it doesn’t consider the arrival time of vehicles. To overcome this problem an adaptive and
intelligent traffic control system is proposed in such a way that a traffic signal controller with wireless radio
installed at the intersection and it is considered as an infrastructure. All the vehicles are equipped with onboard
location, speed sensors and a wireless radio to communicate with the infrastructure thereby VANET is formed.
Once the vehicles enter into the boundary of traffic area, they broadcast their positional information as data
packet with their encapsulated ID in it. The controller at the intersection receives the transmitted packets from
all the legs of intersection and then stores it in a temporary log file. Now the controller runs Platooning
algorithm to group the vehicles approximately in equal size of platoons. The platoons are formed on the basis of
data disseminated by the vehicles. Then the controller runs Oldest Job First algorithm which treats platoons as
jobs. The algorithm schedules jobs in conflict free manner and ensures all the jobs utilize equal processing time
i.e the vehicles of each platoons cross the intersection at equal delays. The proposed approach is evaluated
under various traffic volumes and the performance is analyzed.
Keywords Conflict graphs, online job scheduling, traffic signal control, vehicular ad hoc network (VANET)
simulation, vehicle-actuated traffic signal control, Webster’s algorithm.
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.
Autonomous Traffic Signal Control using Decision Tree IJECEIAES
The objective of this paper is to introduce an effective and efficient way of traffic signal light control to optimize the traffic signal duration across each lanes and thereby, to minimize or completely eliminate traffic congestion. This paper introduces a new approach to resolve the traffic congestion problem at junctions by making use of decision trees. The vehicle count in the real time traffic video is determined by Image Processing technique. This information is fed to the decision tree based on which the decision is made regarding the status of traffic signal lights of each lane at the junction at any given instant of time.
A Framework for Dynamic Traffic Monitoring using Vehicular Ad-hoc Networkshadiarbabi
PhD Defense Presentation
Hadi Arbabi
PhD in Computer Science
Department Of Computer Science
Old Dominion University
Advisor: Dr. Michele C. Weigle
M.S. in Computer Science
Old Dominion University, May 2007 Advisor: Dr. Stephan Olariu
B.S. in Computer Engineering
Shiraz University , June 2001
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
: This paper is aimed at designing a density based dynamic traffic signal system where the timing
of signal will change automatically on sensing the traffic density at any junction using the IoT technology. Traffic
congestion is a severe problem in most cities across the world and therefore it is time to shift more manual mode
or fixed timer mode to an automated system with decision making capabilities. To optimize this problem, we have
made a framework for an intelligent traffic control system. Sometimes higher traffic density at one side of the
junction demands longer green time as compared to standard allotted time. We therefore propose here a
mechanism in which the time period of green light and red light is assigned on the basis of the density of the
traffic present at the time. This is achieved by using LIDAR sensors.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
PTV Vissim is rounded off with comprehensive analysis options, creating a powerful tool for the evaluation and planning of urban and extra-urban transport infrastructure.
ETC ASSISTED TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING VEHICLES’ CO2 EMISSIONSIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light
control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road
conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A
decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then
the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption
and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted real-
time traffic light control scheme has much better performances in reducing the average waiting time,
improving non-stop passing rate, and reducing CO2 emission.
Etc assisted traffic light control scheme for reducing vehicles co2 emissionsIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted realtime traffic light control scheme has much better performances in reducing the average waiting time, improving non-stop passing rate, and reducing CO2 emission.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Describe the main characteristics of the Sydney Coordinated
Adaptive Traffic System (SCATS) and its use in 3 worldwide
cities. Clarification and explanation about the system and
making a comparison between three large cities that use
this system and detailing the advantages and
disadvantages of this system in each city that used it.
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.
A Framework for Dynamic Traffic Monitoring using Vehicular Ad-hoc Networkshadiarbabi
PhD Defense Presentation
Hadi Arbabi
PhD in Computer Science
Department Of Computer Science
Old Dominion University
Advisor: Dr. Michele C. Weigle
M.S. in Computer Science
Old Dominion University, May 2007 Advisor: Dr. Stephan Olariu
B.S. in Computer Engineering
Shiraz University , June 2001
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
A VISION-BASED REAL-TIME ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM USING VEHICULA...JANAK TRIVEDI
In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method.
: This paper is aimed at designing a density based dynamic traffic signal system where the timing
of signal will change automatically on sensing the traffic density at any junction using the IoT technology. Traffic
congestion is a severe problem in most cities across the world and therefore it is time to shift more manual mode
or fixed timer mode to an automated system with decision making capabilities. To optimize this problem, we have
made a framework for an intelligent traffic control system. Sometimes higher traffic density at one side of the
junction demands longer green time as compared to standard allotted time. We therefore propose here a
mechanism in which the time period of green light and red light is assigned on the basis of the density of the
traffic present at the time. This is achieved by using LIDAR sensors.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
PTV Vissim is rounded off with comprehensive analysis options, creating a powerful tool for the evaluation and planning of urban and extra-urban transport infrastructure.
ETC ASSISTED TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING VEHICLES’ CO2 EMISSIONSIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light
control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road
conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A
decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then
the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption
and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted real-
time traffic light control scheme has much better performances in reducing the average waiting time,
improving non-stop passing rate, and reducing CO2 emission.
Etc assisted traffic light control scheme for reducing vehicles co2 emissionsIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted realtime traffic light control scheme has much better performances in reducing the average waiting time, improving non-stop passing rate, and reducing CO2 emission.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Describe the main characteristics of the Sydney Coordinated
Adaptive Traffic System (SCATS) and its use in 3 worldwide
cities. Clarification and explanation about the system and
making a comparison between three large cities that use
this system and detailing the advantages and
disadvantages of this system in each city that used it.
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.
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.
The International Journal of Engineering and Science (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.
The International Journal of Engineering and Science (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.
The International Journal of Engineering and Science (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.
The International Journal of Engineering and Science (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.
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.
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.
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.
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.
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.
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.
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.
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
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
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.
Traffic congestion is diagnosed as principal problems in current urban regions, that have triggered an awful lot uncomfortable for the ambulance to journey. Moreover, road accidents in the city have been increasing and to bar the loss of life due to accidents is even more crucial because the range of automobiles grows hastily each 12 months, more and more traffic congestion happens, turning into a huge trouble for civil engineers in almost all metropolitan cities. Emergency Vehicle Pre-emption systems play a key role in reprioritizing signalized traffic intersections.
This role is essential for safe and minimal travel put off of Emergency vehicles (EV) passing through avenue intersections. This paintings especially objectives on presenting answer for the problem faced via ambulances which can be transferring toward the visitors sign for the duration of excessive density visitors.
Online Accessable Traffic Control System for Urban Areas Using Embedded Syste...IJSRD
During recent years traffic congestion is become a serious problem in almost all cities. Due to the high density of traffic, pedestrians find it difficult to cross the road. Even though several advanced strategic plans are introduced to regulate the traffic but due to lack of provision for on- road pedestrian crossing, rate of accidents become very high. One such provision is given is elevated path for pedestrian to cross the road, but the elderly person finds it difficult to use that. Hence an idea is proposed to help the elderly people by giving provision for on- road pedestrian crossing in high density traffic areas like near schools, hospitals, markets, etc. which reduces the accidents rate also. To implement this, here an additional time delay is introduced in the traffic signal for pedestrian crossing in addition to vehicle crossing in all possible direction. Additionally, provision is given to track the vehicle which violates the traffic rules and to clear the traffic for emergency vehicles. All the above said three parameters can be simulated by using PROTEUS software.
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
A Hybrid Method for Automatic Traffic Control MechanismMangaiK4
Abstract—Traffic control method is an interconnection of sign devices positioned at road intersections, pedestrian crossings and different locations to manage competing flows of traffic. This work provides a novel idea and application procedures of priority and round robin scheduling algorithms. These algorithms methodologies are combined and a new hybrid automatic traffic control mechanism is proposed for efficient traffic and transportation management systems. This mechanism is necessary and it may be applied to modern cities wherever particular paths have more traffic jam compared to other paths of signal and wherever equal or normal traffic. This proposed hybrid approach applies priority scheduling concept to specific paths which has more traffic, on the other hand, this hybrid approach uses round robin scheduling concept for normal traffic signals. This mechanism is well suited for controlling the traffic of modern and old cities,both pre planned and not pre planned before construction. Some general conclusions and promising future research topics are also provided.
Traffic Congestion Prediction using Deep Reinforcement Learning in Vehicular ...IJCNCJournal
In recent years, a new wireless network called vehicular ad-hoc network (VANET), has become a popular research topic. VANET allows communication among vehicles and with roadside units by providing information to each other, such as vehicle velocity, location and direction. In general, when many vehicles likely to use the common route to proceed to the same destination, it can lead to a congested route that should be avoided. It may be better if vehicles are able to predict accurately the traffic congestion and then avoid it. Therefore, in this work, the deep reinforcement learning in VANET to enhance the ability to predict traffic congestion on the roads is proposed. Furthermore, different types of neural networks namely Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are investigated and compared in this deep reinforcement learning model to discover the most effective one. Our proposed method is tested by simulation. The traffic scenarios are created using traffic simulator called Simulation of Urban Mobility (SUMO) before integrating with deep reinforcement learning model. The simulation procedures, as well as the programming used, are described in detail. The performance of our proposed method is evaluated using two metrics; the average travelling time delay and average waiting time delay of vehicles. According to the simulation results, the average travelling time delay and average waiting time delay are gradually improved over the multiple runs, since our proposed method receives feedback from the environment. In addition, the results without and with three different deep learning algorithms, i.e., CNN, MLP and LSTM are compared. It is obvious that the deep reinforcement learning model works effectively when traffic density is neither too high nor too low. In addition, it can be concluded that the effective algorithms for traffic congestion prediction models in descending order are MLP, CNN, and LSTM, respectively.
TRAFFIC CONGESTION PREDICTION USING DEEP REINFORCEMENT LEARNING IN VEHICULAR ...IJCNCJournal
In recent years, a new wireless network called vehicular ad-hoc network (VANET), has become a popular research topic. VANET allows communication among vehicles and with roadside units by providing information to each other, such as vehicle velocity, location and direction. In general, when many vehicles likely to use the common route to proceed to the same destination, it can lead to a congested route that should be avoided. It may be better if vehicles are able to predict accurately the traffic congestion and then avoid it. Therefore, in this work, the deep reinforcement learning in VANET to enhance the ability to predict traffic congestion on the roads is proposed. Furthermore, different types of neural networks namely Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are investigated and compared in this deep reinforcement learning model to discover the most effective one. Our proposed method is tested by simulation. The traffic scenarios are created using traffic simulator called Simulation of Urban Mobility (SUMO) before integrating with deep reinforcement learning model. The simulation procedures, as well as the programming used, are described in detail. The performance of our proposed method is evaluated using two metrics; the average travelling time delay and average waiting time delay of vehicles. According to the simulation results, the average travelling time delay and average waiting time delay are gradually improved over the multiple runs, since our proposed method receives feedback from the environment. In addition, the results without and with three different deep learning algorithms, i.e., CNN, MLP and LSTM are compared. It is obvious that the deep reinforcement learning model works effectively when traffic density is neither too high nor too low. In addition, it can be concluded that the effective algorithms for traffic congestion prediction models in descending order are MLP, CNN, and LSTM, respectively.
Lan based intelligent traffic light system with emergency service identificationIjrdt Journal
In this paper we implemented a traffic lights control system using LAN technology which has the capability of mimicking human intelligence for controlling traffic lights. It aims to do analysis, design, develop and deploy monitoring and information system jointly with the help of state of the art traffic equipment, to enable the safe and efficient and effective movement of traffic for all road users. In this work we implemented the first based on LAN networking. The aim of this paper is to design and implement the network based car traffic control system. This system mainly comprises of signalized junctions and central computer (sever) that is connected to every traffic signal junction (clients). Its main task is to adjust, in real times, signal timings in response to variation in traffic demand and system capacity. Real time data from traffic controls are collected and transported to a central computer (server) for analysis. The results of this work are reduction in normal recurring, significantly enhanced operational tools congestion to effectively manage traffic incidents, reduced pollution, faster response to reports of faults, improved public transport service, reduction in emergency response times and safer travel and less congestion during road works.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
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GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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https://arxiv.org/abs/2306.08302
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UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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The International Journal of Engineering and Science (The IJES)
1. The International Journal Of Engineering And Science (IJES)
||Volume||2 ||Issue|| 7 ||Pages|| 39-45||2013||
ISSN(e): 2319 – 1813 ISSN(p): 2319 – 1805
www.theijes.com The IJES Page 39
Using Polygamy Technology with FL, GA and NN On Traffic
Lights
1,
Mohammad ALODAT , 2,
IYAS AL-ODAT
1,2,
University of Craiova, Automation Department, Craiova, Romania
--------------------------------------------------------ABSTRACT-----------------------------------------------------------
recently, multi agent system was developed intelligent techniques through polygamy with Fuzzy logic
(FL), Artificial neural network (NN) and genetic algorithm(GA) therefore, a combination has led to the
emergence of Fuzzy Neural Network (FNN) and Genetic Fuzzy System (GFS), and has a hard challenge
because these polygamy design of intelligent systems from different aspects. Each agent uses a multi stage
process of learning direct, decision making mechanism and update, adapt their knowledge base, Knowing that
he mechanisms learning form the basis for adaptive systems. FNN is a has advantages of both fuzzy expert
system become capable of learning (fuzzy reasoning) and artificial neural network become more transparent
(self-adapting, self-organizing and self-learning). Compared with traditional control methods for traffic signal
find better resolution for optimize is a genetic algorithm. The genetic learning process aims at designing and
optimizing the knowledge base. The genetic process is the result of the interaction between the evaluation,
selection and creation of genetically encoded candidate solutions, which represent the contents of the
knowledge base (KB). The traffic signals control, there are a number of diverse criteria or control objectives,
such as maximize safety, minimize delays and minimize environment disadvantage.
KEYWORDS:Fuzzy logic, Fuzzy Neural Network, Genetic Algorithm, genetic fuzzy systems.
-------------------------------------------------------------------------------------------------------------------------------------
Date of Submission:, 13, july 2013 Date of Publication: 30.july 2013
-------------------------------------------------------------------------------------------------------------------------------------
I. INTRODUCTION
Increase the owners of cars and population expansion leading to an increase in intersections and the
rate of the vehicles on the roads. Then a danger of the vehicles has appeared and they began Collision and left
many victims. Human mind began thinking of way that can decrease the accidents by organizing the
movement of vehicles and pedestrians on the roads. Then it came the birth of the first scientific method, it was
the traffic light. conventional methods for traffic signal control but most of them sometimes fail to deal
efficiently with the complex, time-varying traffic conditions and controller can’t satisfy real-time character for
traffic signal [8].They are modelled based on the preset cycle time to change the signal without any analysis of
traffic situation. It gives the orders to drivers by three lights, red, orange, and green. The red Colour means the
Drivers of Vehicles must stop. The orange Colour means the Drivers of Vehicles must ready that the colour
will change from red to green. The green Colour means the Drivers of Vehicles must go. The automotive
industry has flourished and the national product output increased to states .The level of income of the
individual increased and became one of ten people has a vehicle or perhaps more. The roads are filled with
pedestrians and vehicles, and the traffic light became unable to organize them because of congestion. So this
congestion has forced some states to give up the traffic light in the congested places and resorting to build
tunnels and elevated bridges .This solution faced many obstacles in some states and it cannot be applied inside
them. And they are: Firstly, it needs a lot of money that it is costly to their budget. Secondly, it is very
dangerous in states that are known of earthquakes .Thirdly, it is very dangerous in states that their roads are
above natural sites such as rivers. But we can overcome these obstacles by developing the traffic light that
make it work on the agent. Sometime lanes are empty of vehicles at the intersection of roads while the other
lanes are filled by them according to the working hours and direction. For example: In the morning, the lane
which is heading to the work that is standing on the traffic light is too long line, but another lane is empty.
And the same thing In the evening At the end of work .If we are able to make the traffic light interacts with
congestion by opening congested lanes for a longer time .This way will achieve a great achievement in this
2. Using Polygamy Technology With FL…
www.theijes.com The IJES Page 40
field and save time, effort, and money .To alleviate traffic congestion in urban areas, the concept of Intelligent
Transportation Systems (ITS). ITS is a highly promising system for providing key solutions to current road
congestion problems [6]. The use of traditional methods and not to improve the performance of urban traffic
signal control system to the road conditions are effective modeling and control because of the vagaries of time,
non-linear, fuzzy and non-determinism in the system. Rapidly developing of artificial intelligence (AI) field
can access to Adaptive this mean urban area traffic signals coordinated control system, it is supposed to
respond to traffic demand and online optimum timing plans in time, and then implement real-time control.
Recently, major research on urban traffic focuses on artificial intelligence techniques, such as fuzzy control,
genetic algorithm and neural network [2][7]. Fuzzy logic controller for an isolated intersection, obtained
intersection fuzzy control parameters from neural networks, and improved fuzzy control result [3][4][18].
Traffic signal control intersection signal (adjacent intersection) with fuzzy algorithm, and updates fuzzy
control rules with genetic algorithm. The length of current green phase is extended or terminated depending to
Arrival is number of vehicle approaching the green phase and Queue is that corresponds to the number of
queuing vehicles in red or green phases. A GFS is basically a fuzzy system augmented by a learning process
based on evolutionary computation, which includes genetic algorithms, genetic programming, and evolutionary
strategies, among other evolutionary algorithms (EAs) [1]. The multi agent systems evaluated two things delay
of vehicles and stoppage time of vehicles. Where, reduce total traffic delay by adjusting parameters such as
cycle, splits, phase sequences and offsets according to changes of the traffic volume.
II. FUZZY LOGIC SYSTEMS
Fuzzy logic is easy, very suitable for non-linear processes and ability to take decision even with
incomplete information, such as traffic police man can lead traffic quickly and effectively. Fuzzy logic allows
the manipulation of linguistic data (Large, Medium and Small) and inaccurate, as a useful tool in the design of
signal timing. In this paper, function of Membership is analysis variable of fuzzy for two inputs and one
output as it is shown: 1) Variable of Input AVi is the numbers of the vehicles when they arrive at the crossroad
(Arrival).2) Variable of Input QGi is the number of the queue of vehicles (Queue). 3) Variable of Output is the
Extension of Time in the current green phase, it is symbolize by (ΔT) [9]. The graphical representation of the
linguistic variables is presented as it is shown in Figure 3. we can see the Degree of membership of fuzzy
variables on y-axis and the universe of discourse it is also called the reference super set on x-axis (Time
second) . Fuzzy Variable of Output which is existed in x-axis it is called the universe of discourse is the length
of time to extend it (seconds). linguistic values are divided into different fuzzy subsets: 1)AVi = {VS, S, M, L,
VL}.2) QGi= {VS, S, M, L, VL}.3) ΔT= {D, C, I}. VS is Very Small, S is Small, M is Medium, L is Large,
VL is Very Large, D is Decrease, C is Constant, I is Increase. i refers to the sequence number of the signal
current phase. the linguistic control strategy that is decided by “if-then-else” statement .The basic function of
The Basic Rules of Fuzzy is representation the expert of knowledge in a form of IF-THEN a structure of the
rules combine AND/OR operators. We have 25 fuzzy rules, IF the number of vehicles which are waiting in line
or queuing (Q) is medium AND the number of vehicles which arrive or arrival (A) is small THEN the
allocated time for the green light (T) decreases [13]. Inference Engine divides into two classes: the first class is
an assignment of the Inference and the second class is mechanism of action Inference. An assignment of the
Inference, it reduces time of the total delay and waiting of vehicles as well as to avoid traffic congestion and
synchronization of the local traffic controller with its neighbours. The green lights will be extended and the
next phase is continued with notice the density of the vehicles at any junction. The mechanism of action
Inference, the fuzzy inference evaluates the stored rules in the basic rules of fuzzy and then sending it to
Defuzzification. Its job is process of input functions of Membership (AVi, QGi) to convert (retranslate) values
the fuzzy output (ΔT) to become real crisp values. Fuzzy logic cannot be learning, adaptation, and parallel
computing, while these effects exist in neural networks. Because lack of flexibility of neural network
interaction and representation of knowledge using fuzzy logic.
III. THE GENETIC ALGORITHM (GA) AND GENETIC FUZZY SYSTEMS (GFS)
Genetic algorithms (GAs) try to perform an intelligent search to find a solution from a nearly infinite
number of possible solutions by creating new generations. It is obtained from Darwin's Theory which means
the law of the jungle (survival of the fittest). Genetic algorithms)GAs( are able to explore a large space , find
better offspring (children) in complex search spaces during successive generations by a new generation and it
has to be better than the previous generation. Genetic algorithms (GAs) processes for selecting solutions
consist of three operators and they are: reproduction, crossover and mutation where all of them are existed in
genetics.
3. Using Polygamy Technology With FL…
www.theijes.com The IJES Page 41
The advantage of producing process of a new generation: 1) the evaluation which is repeated in order
to reach to a better generation. 2) It searches for a solution from a broad range of possible solutions for giving
expected results instead of searching in a narrow domain. The Genetic algorithm)GAs( describes attempts in
order to arrive to perfect search in vacant spaces in parked vehicles such as medium speed, maximum speed,
vehicle location, desired speed, current acceleration ,The proper angle of the vehicle and wheel, unique number
for selecting the vehicle identification ,traffic standstill, resume motion, and return to standstill again, and so
on. The genetic learning process aims for designing and optimising the knowledge base (KB). The knowledge
base (KB) consists of two components and they are: 1) a database (DB) which consists of the linguistic rules
and the functions of the membership. 2) Rule base (RB) that means multiple rules simultaneously for the same
input. The use of The Genetic algorithm for automatic learning of Basic Rules of Fuzzy systems (BRFS) can
optimize search problem and the design process can be analysed as a search problem in the space of rule sets
by coding of the chromosome model.
Shortcomings BRFS are not able to learn, but it needs knowledge base (KB), which is derived from
expert knowledge. BRFS are analysis process as a search problem in the space of rule sets, through coding of
the model in a chromosome and the most extended in GFS .it is used the genetic Basic Rules of Fuzzy systems
(GBRFS). The genetic fuzzy systems (GFS) [12] are used for designing fuzzy systems. They provide them the
learning, adaptation capabilities and sharing in the genetic learning process [1][11]. GBRFS Support
technological development more than BRFS for achieving the automatic generation, modification or part of the
knowledge base) KB( . The Genetic algorithm (GA) is executed to obtain the best possible solution and steps of
algorithm are initialize population, evaluate population, chromosomes selection and chromosomes
recombination. This is done by arranging the elements of the chromosome in increasing values which is given
by the Fitness Function (σi). It can measure throughout the total driving and waiting times. The genetic
process is the result of the interaction among the evaluation, selection and creation of solutions, which
represents the contents of the knowledge base (KB) of a BRFS. As it is shown in figures 1.
Figure 1: (A), General Scheme of Evolutionary process in genetic with Fuzzy (GFS). (B), Example of
genetic with Fuzzy (GFS) and rule selection.
IV. FUZZY NEURAL NETWORK
Artificial neural network (ANN)[5] By integrating the two approaches ANN with Fuzzy call Neural
fuzzy network (FNN), it is possible to overcome the deficiencies associated with using a single approach
(ANN or Fuzzy) .FNN using to solve the real time arterial coordinated control problem on road. Researchers
have long felt that the neurons are responsible for the human capacity to learn. Aiming to develop new
architectures to improve learning and skills upgrading of knowledge representation. Incorporating FL into the
NN allows a cognitive uncertainty in a similar way to treat humans. Having the potential of parallel
computation with high flexibility become machine more intelligent and effectively with the increasing
complexity of congestion road. Neural fuzzy network (FNN) could be as a rule-like NN. A network that
topologically is structured as a rule-based system with "IF-THEN" clauses, vagueness of defining complexity
classes that can be processed and solved using concepts of fuzzy logic. Learning systems use artificial neural
network (ANN) calculate decisions by learning from successfully solved optimal [15]. Learning system such as
ANN, knowledge is represented in the form of weighted connections, making decision tracing or extraction
difficult. Expert system is knowledge-based systems extensively explored as approaches for decision making
where rely on a knowledge base developed by human reasoning for decision making. Acceptability of the
4. Using Polygamy Technology With FL…
www.theijes.com The IJES Page 42
solution and correctness of the reasoning process by evaluating the trace generated by the inference engine or
analysing the rule base (use “IF THEN” rules). The main features of FNN [8].
the accurate learning
adaptive capabilities of the neural networks
Generalization and fast-learning capabilities of fuzzy logic systems.
The fuzzy neural network [3] that is used in our work is a five-layer neural network as shown in
Figure 2 designed according to the working process of fuzzy controller systems. We explain how a neural
network can be used to determine membership functions. A neural network is a technique that seeks to build
an intelligent program to implement intelligence .The relation and functions of the nodes in the network are as
follows.
4.1. The first layer
Input layer consists of two nodes, the input linguistic variables QGi and AVI. The first layer can be
written as
AVi=N1
1 , QGi=N1
2 (1).
4.2. The Second layer
Membership function layer consists of ten nodes. Each node in this layer represents the membership
function of a linguistic value associated with an input where linguistic variable is {VS, S, M, L, VL}.The
output of each node in the interval [0, 1] Gaussian function [4] is used to divide the output signal of each node
is:
= (2).
Where αjk and bjk are parameters that control the centre and the width of the Triangle , respectively.
Parameters will be adjusted in back propagation. wi
jk represents the weight associated with the path
connecting the jth element of the i
th layer to the kth element of the (i + 1)th layer. Show appendix I.
4.3. The Third Layer
Fuzzy rules are the relationship between ex ante and ex post , and each action is a set of fuzzy rules
organized and composed Fuzzy 25 of the rules. Node of the third layer of computing fire combiner rule is
interpreted in accordance with the rules as proposed minimum operator Zadeh [5]. Result of this layer can be
represents as
N3
p =Min (Njk) (3).
Where p=1...25. p is the number of rules; we have 25 rules in our work.
4.4. The forth layer
The relationship between third and fourth layers is fully connected, so that all possible fuzzy rules, the
embedded network structure. The weight αp (1≤p≤25) of an input link in the layer represents the certainty
factor of a fuzzy rules. These weights are adjusted fuzzy rules to learn the knowledge. We choose the max-
operator suggested by Zadeh [5] the results of this layer.
N4
j=Max(αp.Np) ,where j=1,2,3. (4) .
4.5. The fifth layer
This layer is called defuzzification [6]. Node in this layer is the output linguistic variables and
performs defuzzification . We chose the final product of the correlation and fuzzy defuzzification focus
position and function of the output node is defined as follows:
N= / (5).
Where aj and bj are the area and centroid of the membership function of the output linguistic value
respectively.
5. Using Polygamy Technology With FL…
www.theijes.com The IJES Page 43
Figure 2: Model of Fuzzy Neural Network.
V. GENETIC WITH FNN
The most popular approaches to machine learning are artificial neural networks and genetic
algorithms. Determine the optimal learning using GA with FNN. We see more problems with the back-
propagation algorithm with GA are connected instead of back propagation as a way to find a good set.
Back−propagation on a given training example consists of two parts 1) the forward propagation of activation
and the calculation of errors at the output units 2) the backward error propagation and adjusting of the weights,
the second part requires more computation. Moreover GA takes less than half the computation of
back−propagation iteration. Only alleles representing different layers and having a binary value of one (1) are
connected to one another. Shows a possible mapping of a chromosome to antecedent– implication relations;
shown in figures 3.
Figure 3: Model of Genetic Fuzzy Neural in hidden layer
VI. FORMATION OF FNN NETWORK WITH GENETIC ALGORITHM
The Traffic Management system is designed scientifically for provide an optimum throughput of
vehicles through an intersection. Traffic signal control strategy is provided using genetic algorithms to provide
near optimal traffic performance for intersections. To reduce classification error, it is necessary to improve the
compression system with feedback from the classifier [10]. We use the genetic algorithm to choose the best
filter coefficients in ADPCM. The fitness function which measures the ADPCM filter performance is the pre-
and post-ADPCM classification error. ADPCM predictors are tested to minimize the least mean square (LMS)
is a very simple algorithm, and a good choice to update the predictor. Mean square based adaptive algorithm
that aims to minimize the squared error in prediction [8]. Genetic algorithm is used to minimize the least mean
square (LMS) between the actual data and the predicted data is.
E (n) =Δt(n)- ΔṰ(n). (6).
Where Δt(n) The signal to be transmitted or stored. ΔṰ (n) the output of the adaptive predictor. ḙ (n) The
quantized error to be transmitted or stored. Construct the training algorithm
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1. The time of traffic light and converted to the system code Gray.
2. Define squared error as fitness function of GA and FNN weights as its variables.
3. Produce an initial population of individuals.
4. Evaluate the fitness of all individuals’ Select fitter individuals for reproduction Recombine between
5. individuals Mutate individuals Evaluate the fitness of the modified individuals Generate a new population.
Check, if a termination criterion is satisfied. Get the solution (the current generation). Termination criterion is
set to stop the working of algorithm. Usually, it is set to a fix number of generation. Maturity level can also be
used as termination criteria
VII. SIMULATION AND RESULTS
7.1. The Intersection
Intersection consists of four ways, two-lane junction hence eight lanes and it has an entry node, an
exit node for each lane and one intersection node (junction). An isolated signalized intersection with four-legs
in each leg and Traffic signal is controlled by four phases. Decisions were made every 10 seconds to decide.
Minimum of cycle is about 20 seconds and maximum of cycle is about 820 seconds so Max Phase 205 Seconds.
.
7.2. Simulation
The Criterion of optimization is the decrement length of queues and the average of waiting time
vehicles in intersection. The minimum green time is preset as 5 seconds in order to let the vehicles cross the
intersection safely. The maximum of the extension of green time is 40 seconds. The parameters of this GA are
set as: Population size=200, crossover probability=0.5, mutation probability=0.01[14].
7.3. Results
For testing our traffic control system, we compare results fuzzy systems (FS) and genetic algorithms
(GA) control with fixed time control system (static control) it is shown figure 9. Results show that it could
shorten the queue, and reduce total traffic delay. We did this experiment on 1000 vehicles in intersection it is
shown in table I and shown in figures 4, 5.
TABLE I: Waiting Time Comparison for 1000 Vehicles
Control Method Average Waiting Time(second)
Fixed Time Control 217 s
FNN control with BP 65 s
FNN control with GA 33 s
Figure 4: Comparison of Fuzzy Systems (FS), Neural Networks (NN) and Genetic Algorithms (GA).
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Figure 5: Fitness Generation
VIII. CONCLUSION
In this paper multi agent system demonstrates clearly superior performance for the 24-h .we applies
the Fuzzy Neural Network (FNN) model to traffic signal controller. The most popular approaches to machine
learning are artificial neural networks and genetic algorithms. Machine learning mechanisms form the basis
for adaptive systems. So machine learning involves adaptive mechanisms that enable computers to learn from
experience, learn by example and learn by analogy. Artificial neural fuzzy network models can be powerful
predictors of the timing of traffic on intersection. Genetic algorithms are able to evolve predictive equations,
either randomly synthesized or in the framework of existing process equations. We use genetic algorithm for
learning process and choose the best filter coefficients in ADPCM By the learning of the neural network, we
can tune the fuzzy model and optimize system’s parameters. The research results have proved feasibility and
validity of the proposed FNN algorithm.
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