scholarly journals Scheduling of Traffic Entities Under Reduced Traffic Flow by Means of Fuzzy Logic Control

2021 ◽  
Vol 33 (4) ◽  
pp. 621-632
Author(s):  
Zdenko Kljaić ◽  
Danijel Pavković ◽  
Tomislav Josip Mlinarić ◽  
Mladen Nikšić
Keyword(s):  
Fuzzy Logic ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Probability Distributions ◽  
Scheduling Algorithm ◽  
Green Light ◽  
Transportation Systems ◽  
Traffic Scheduling ◽  
Traffic Lane ◽  
Queue Lengths

This paper presents the design of a fuzzy logic-based traffic scheduling algorithm aimed at reducing traffic congestion for the case of partial obstruction of a bidirectional traffic lane. Such a problem is typically encountered in rail traffic and personal rapid transportation systems with predefined and fixed traffic corridors. The proposed proportional-derivative (PD) fuzzy control algorithm, serving as a traffic control automaton, alternately assigns adaptive green light periods to traffic coming from each direction. The proposed fuzzy logic-based traffic controller has been compared with the conventional traffic control automaton featuring fixed-durations of green light intervals. The comparison has been carried out within a simulation environment for four different probability distributions of stochastic traffic flows at each end of the considered traffic corridor. Results have shown that the proposed fuzzy logic-based traffic controller performance is far superior to that of the conventional traffic control law in terms of achieving shorter vehicle queue lengths and less disparity in queue lengths for all considered simulation scenarios.

scholarly journals DYNAMIC BEHAVIOUR OF A MODELED TRANSPORTATION NETWORKED CONTROL SYSTEM FOR T-JUNCTION

2017 ◽  
Vol 16 (1) ◽  
pp. 70-82
Author(s):  
O. O. NUGA ◽  
K. A. AMUSA ◽  
A. J. OLANIPEKUN ◽  
A. ADEWUSI
Keyword(s):  
Fuzzy Logic ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Fuzzy Logic Controller ◽  
Green Light ◽  
Fixed Time ◽  
Networked Control System ◽  
Urban Migration ◽  
Smooth Flow ◽  
Traffic Signal Timing

Traffic congestion has been the major problem on most Nigeria roads. This is particularly due to the rapid increase in urban migration. Majority of the traffic control schemes adopted in the country to alleviate this problem are the fixed time controllers employed at all signalized intersections. This has resulted in increased traffic jam especially during the peak periods at most intersections on our highways. In this study, a fuzzy logic system to control traffic on signalized intersection has been proposed. The Fuzzy Logic Controller regulates the traffic signal timing, the green light extension and phase sequence to ensure smooth flow of traffic, thereby reducing traffic delays and thus increasing the intersection capacity. A fuzzy logic traffic control simulation model was developed and tested using MATLAB/ SIMULINK software. Comparative analysis was carried out between the fuzzy logic controller and a conventional fixed-time controller in order to determine the efficiency of the developed system. Evaluation results of the fuzzy logic traffic controller shows that vehicles spent less time at the intersection compared to the fixed time controller, that is, improved vehicular movement. Moreover, simulation results show that the fuzzy logic controller has better efficiency and that a huge improvement could be realized by adapting it in controlling traffic flow at intersections.  

scholarly journals TRAFFIC LIGHT CONTROL USING FUZZY LOGIC MAMDANI METHOD

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Traffic Congestion ◽  
Green Light ◽  
Light Control ◽  
Traffic Light ◽  
Additional Time ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Traffic Light Control

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time

scholarly journals An Intelligent Fuzzy Logic Based Traffic Controller

2020 ◽  
Keyword(s):  
Fuzzy Logic ◽  
Cycle Time ◽  
Traffic Congestion ◽  
Carbon Dioxide Emissions ◽  
Road Traffic ◽  
Green Light ◽  
Traffic Lights ◽  
Road Congestion ◽  
Light Duration ◽  
Matlab Programming

Increasing road congestion, travel time, number of accidents, carbon dioxide emissions, and fuel consumption are some of the consequences of growth in the vehicle population. Therefore, intelligent traffic controllers are required to solve road traffic congestion problems. The results of prevalent methods, including preset cycle time controller and vehicle-actuated controller, indicated that they do not effectively perform at traffic peak moments. Therefore, due to the deficiency of common methods, fuzzy logic based traffic signal controllers have attracted a lot of attention among researchers. In this article, a fuzzy logic based algorithm for 4-way intersections is proposed and it consists of two main stages for sorting the phase and determining the green light duration. The proposed system is simulated in the MATLAB programming environment and the performance of the designed controller and a conventional controller is compared for some of the presumed conditions. The results of applying the proposed system indicate that this algorithm has a better performance in different traffic conditions in contrast to a preset cycle time controller and it can reduce the number of vehicles behind traffic lights at intersections and the waiting time of passengers.

Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference

2013 ◽  
Vol 397-400 ◽  
pp. 2227-2230
Author(s):  
Ming Long Peng ◽  
Xin Rong Liang ◽  
Chao Jun Dong ◽  
Yan Yan Liu
Keyword(s):  
Fuzzy Logic ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Weather Conditions ◽  
Freeway Traffic ◽  
Fuzzy Logic Inference ◽  
Identification Method ◽  
Congestion Detection ◽  
Congestion Index ◽  
Logic Inference

Traffic congestion detection is the basis of dynamic traffic control and real time guidance. This study proposes a fuzzy logic based traffic congestion identification method. The components of a fuzzy logic inference are firstly formulated. According to such information as the speed and occupancy of freeway traffic flow, and the weather conditions on the freeway, a congestion identification method based on fuzzy logic inference is then designed. Gauss curves are assumed for the membership functions of the input and output variables, and 45 fuzzy rules are also established. Finally, the congestion identification method is simulated. Simulation results verify the effectiveness of the above method. Fuzzy logic inference is suitable for estimating the traffic congestion index.

scholarly journals Fuzzy-based quantification of congestion for traffic control

2021 ◽  
Vol 72 (1) ◽  
pp. 1-8
Author(s):  
Dinh Toan Trinh
Keyword(s):  
Fuzzy Logic ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Fuzzy Rule ◽  
Gradual Transition ◽  
Rule Base ◽  
State Variables ◽  
Study Results ◽  
Traffic Stream

This paper presents a methodology for appraisal of congestion level for traffic control on expressways using fuzzy logic. The congestion level indicates the severity of congestion and is estimated using speed and density, being the basic traffic parameters that describe state of a traffic stream. Formulation of the fuzzy rule base is made based on knowledge on traffic flow theory and engineering judgments. Field data on a segment of the Pan-Island Expressway of Singapore were used to estimate the congestion levels for three scenarios: single input variable (speed or density) and combined input variables (speed and density), represented by congestion level on a [0 1] scale. The results showed that there were big gaps between the congestion levels evaluated based specifically on speed and density alone (single state variable), and the congestion levels estimated from both variables lie in between. Given the uncertainty in traffic data collection and dynamic nature of traffic flow, this indicates that it may be inadequate to evaluate traffic congestion level using a single variable, and the use of both speed and density represent the state of a traffic stream more properly. The study results also show that the fuzzy logic approach provides flexible combination of state variables to obtain the congestion level and to describe gradual transition of traffic state, which is particularly important under the heavy congested conditions.

scholarly journals TRAFFIC LIGHT CONTROL USING FUZZY LOGIC MAMDANI METHOD

2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Traffic Congestion ◽  
Green Light ◽  
Light Control ◽  
Traffic Light ◽  
Additional Time ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Traffic Light Control

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time

scholarly journals IoT Based Automated Traffic Light Control System For Emergency Vehicles Using LoRa

2019 ◽  
Author(s):  
Divij N ◽  
Divya K ◽  
Anuradha Badage
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Accurate Solution ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lane ◽  
Emergency Vehicles ◽  
Scheduled Traffic ◽  
Cost Efficient

There is a serious issue of Emergency Vehicles being stuck at intersections due to traffic congestion or scheduled traffic signal. This may result in delay in motion or the Emergency Vehicle may remain in statutory position. Otherwise, if the emergency vehicle ever tries to override the signal, it may result in accident or traffic congestion. To overcome this problem automated traffic control system is proposed. The system is designed to find a cost efficient and accurate solution to save lives. In the system, siren of the approaching emergency vehicle is priorly sensed by using smart objects and the traffic lane in which the emergency vehicle isapproaching is made free by halting the traffic in other lanes of the intersection.

Research on Congestion Mitigation Strategy Downstream Off-Ramp for Urban Expressway Based on Fuzzy Logic Method

2011 ◽  
Vol 299-300 ◽  
pp. 1271-1274
Author(s):  
Xue Wen Chen
Keyword(s):  
Traffic Congestion ◽  
Fuzzy Controller ◽  
Green Light ◽  
Light Phase ◽  
Simulation Research ◽  
Congestion Mitigation ◽  
Urban Expressway ◽  
Matlab Program ◽  
Fuzzy Logic Method ◽  
Queue Lengths

As the uncertain characteristics of traffic flow in urban expressway, fuzzy control can be used as an effectual way to solve traffic problem. A fuzzy controller of signal intersection is designed for alleviating traffic congestion downstream off-ramp at the Surface Street. The overtime of green-light and the next time for green-light phase are optimized according to the queue lengths and the numbers of phase delay, and the method corresponds to a man’s decision-making process. Simulation research based on MATLAB program design is carried out and the results show that the methods are promising and the fuzzy controller have a better performance for congestion mitigation downstream off-ramp of urban expressway.

Ingenious Traffic Control System with Green Signal Timings Using Image Processing

2020 ◽  
Vol 12 (3) ◽  
pp. 337-341
Author(s):  
Venkateshwaran Ganesh ◽  
C. Sujatha
Keyword(s):  
Image Processing ◽  
Control System ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Green Light ◽  
Daily Routine ◽  
Long Run ◽  
Ir Sensors ◽  
Traffic Control System ◽  
The Voice

In metropolis, traffic congestion affects the daily routine of passengers and in the long run there will be a declination in productivity if such situation is left unaddressed. If an Ambulance, unfortunately, stuck in the middle of congested road, any delay can endanger the life of the patient and, such cases require intelligent, powerful and reliable traffic control system. In this paper, the Infra-Red (IR) Sensors keep track of vehicle density across the lane. The micro-controller in turn, generates the control signals to alter the traffic accordingly. During each transition phase, the Voice Recognition (VR) modules installed on lanes sense the emergency siren and thus temporarily allow passage by turning the signal green for the corresponding lane, while others, being remained at red. Using Image Processing analysis, the exact count of vehicles can be visualized in the Graphical User Interface (GUI) Tool and the green light timings for the consecutive turns can be estimated.

Modified fuzzy-based greedy routing protocol for VANETs

2020 ◽  
Vol 39 (6) ◽  
pp. 8357-8364
Author(s):  
Thompson Stephan ◽  
Ananthnarayan Rajappa ◽  
K.S. Sendhil Kumar ◽  
Shivang Gupta ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Routing Protocol ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Research Area ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Greedy Routing ◽  
Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

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