OPTIMISING TRAFFIC FLOW AT A SIGNALISED INTERSECTION USING SIMULATION

2019 ◽  
Vol 4 (2) ◽  
pp. 261
Author(s):  
Muhammad Rozi Malim ◽  
Faridah Abdul Halim ◽  
Sherey Sufreney Abd Rahman
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Simulation Software ◽  
Traffic Signal ◽  
Traffic Data ◽  
Traffic Light ◽  
Traffic Lights ◽  
Light Management ◽  
Optimal Setting ◽  
Pedestrian Crossing

Traffic signal lights system is a signalling device located an intersection or pedestrian crossing to control the movement of traffic. The timing of traffic signal lights has attracted many researchers to study the problems involving traffic light management and looking for an inexpensive and effective solution that requires inexpensive changes in the infrastructures. A simple traffic lights system uses a pre-timed control setting based on the latest traffic data, and the setting could be manually changed. It is a common type of signal control and sometimes the setting was not correctly configured with the traffic data, thus leading to congestion at an intersection. Many mathematical strategies were applied to get an optimal setting. This study aims to model the traffic flow at Persiaran Kayangan and Persiaran Permai Intersection, Section 7, Shah Alam, as the case study, by using AnyLogic simulation software. The model was used to determine the best timings of traffic green lights that minimise the average time at the intersection and reduce traffic congestion. The findings showed that the best timings of traffic green lights for four directions at the intersection are 120 seconds, 75 seconds, 130 seconds and 100 seconds, respectively. These timings of green lights produced the lowest average time at the intersection (55.65 seconds).

scholarly journals Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction

2014 ◽  
Vol 26 (5) ◽  
pp. 393-403 ◽  
Author(s):  
Seyed Hadi Hosseini ◽  
Behzad Moshiri ◽  
Ashkan Rahimi-Kian ◽  
Babak Nadjar Araabi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Weather Conditions ◽  
Traffic Data ◽  
Data Loss ◽  
Traffic Lights ◽  
Traffic Flow Prediction ◽  
Traffic Flow Forecasting ◽  
Flow Prediction ◽  
Forecasting Method

Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI) technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and future traffic flow. In numerical case studies, the proposed traffic flow forecasting method was tested against data loss, changes in weather conditions, traffic congestion, and accidents. The outcomes were highly acceptable for all cases and showed the robustness of the proposed flow forecasting method.

scholarly journals Exploiting witness for traffic simulation

2014 ◽  
Vol 1 (1) ◽  
pp. 12-24
Author(s):  
Azhar Ismail ◽  
Muhammad Latif ◽  
Mian Awai
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Waiting Times ◽  
Simulation Software ◽  
Peak Time ◽  
Traffic Lights ◽  
Traffic Intersection ◽  
Flow Through ◽  
Alternative Scenarios

Traffic congestion in urban cities is an increasing problem. Not only does it lead to an increase in pollution, but the time spent waiting in traffic queues wastes valuable time in addition to causing frustration. A system that can control and manage traffic efficiently is one way that this issue can be reduced.A specific road traffic intersection in South Manchester, UK, was selected for investigation as it experiences high levels of traffic flow through it during the evening peak time. This has led to large queues and long waiting times due to the fixed timings of the traffic lights. This paper explores strategies to better control the traffic flow through it. A model of the selected traffic junction has been built using Witness simulation software. Data for this junction has been obtained partially from observations and mostly from traffic surveys enabling a simulation of the traffic flow. Analysing the results allowed two alternative scenarios to be developed and simulated. Results from one of the scenarios showed noticeable reductions in the average queue waiting times at the traffic junction.

Smart Traffic Light Management Systems

2020 ◽  
Vol 11 (3) ◽  
pp. 22-47
Author(s):  
Aws Abed Al Raheem Magableh ◽  
Mohanad A. Almakhadmeh ◽  
Nawaf Alsrehin ◽  
Ahmad F. Klaib
Keyword(s):  
Law Enforcement ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Video Data ◽  
Traffic Light ◽  
Infrared Sensors ◽  
Traffic Lights ◽  
Loop Detection ◽  
Light Management ◽  
Smart Traffic

Traffic congestion is a major concern in many cities. Failure to heed signals, poor law enforcement, and bad traffic light management are main factors that have led to traffic congestion. One of the most important problems in cities is the difficulty of further expanding the existing infrastructures. Having that in mind, the main accessible and available alternatives that could provide better management of the traffic lights is to use technological systems. There are many methods available for traffic management such as video data analysis, infrared sensors, inductive loop detection, wireless sensor networks, and a few other technologies. This research is focused on reviewing all these existing methods and studies using a systematic literature review (SLR). The SLR was intended to improve the synthesis of research by introducing a systematic process. This article aims at analyzing and assessing the existing studies against selected factors of comparison. The study achieves these aims by analyzing 78 main studies. The research outcomes indicated that there are decent numbers of studies that have been proposed in the area of smart traffic light management. However, less attention has been paid on the possibility of investigating the use of live traffic data to improve the accuracy of traffic management.

Microcontroller-Based Intelligent Traffic Signal Controller Design

2014 ◽  
Vol 998-999 ◽  
pp. 621-625
Author(s):  
Hong Ke Xu ◽  
Jia Yu Yang ◽  
Ming Qiang Song ◽  
Yong Zhao Qu ◽  
Xiao Hong Wang
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Traffic Signal ◽  
Input Device ◽  
Traffic Light ◽  
Two Phase ◽  
Traffic Condition ◽  
Display Module ◽  
Traffic Lights ◽  
Manual Input

With the road traffic congestion problems become more and more serious, and the current traffic lights don’t possess the function of revising timely and flexible, it can't meet the requirements of real-time controlling and make the traffic in intersection more efficient. The design of Microcontroller-based traffic signal controller fixes this problem. It based on STC90C51 as CPU solutions; LED lights and digital pipe were used as display module; 8 independent keyboards were used as the only manual input device; Software used the C programming language. The intelligent traffic light system covered the multi-phase and multi-period. So we could choose two-phase/four-phase/six-phase according to the particular road and traffic condition. Besides, it took the special status of emergency vehicles into account. It also had a manual input keyboard so that you could adjust the signal at any time. This design can effectively improve the traffic congestion problem.

scholarly journals Simulation of Traffic Optimization to Reduce Congestion

2019 ◽  
Vol 8 (11) ◽  
pp. 3780-3783
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Flow Density ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic System ◽  
Light System ◽  
Intelligent Traffic System ◽  
Traffic Optimization ◽  
Indian Cities

There has been an alarming increase in the number of vehicles on the Indian roads in the recent times, almost triple as that in 2005[10]. which obviously leads to traffic congestion on road and enhanced pollution, although there has been many reasons for the same but major one is unmanaged traffic light system as the current traffic light system is either manual or static timings of traffic lights regardless of the flow of traffic. There is a need for smart solution to the traffic light in Indian cities or to have ITS (Intelligent traffic system). Paper provides a solution based on camera feed at crossings for each lane, process the data through and allocates the “Green” time according to its traffic flow density using YOLO v3 and also takes care of starvation issue that might arise of the solution. As a result the flow of traffic on each lane is automatically optimized and the congestion that used to happen unnecessarily earlier is eliminated and results shows significant benefits in reducing traffic waiting time.

scholarly journals Simulation and Research of Urban Intelligent Traffic Light Control System

2021 ◽  
Vol 2068 (1) ◽  
pp. 012043
Author(s):  
Chunling Sun ◽  
Fuhai Liu
Keyword(s):  
Control System ◽  
Traffic Flow ◽  
Working Hours ◽  
Simulation Software ◽  
Light Control ◽  
Traffic Light ◽  
Safety Control ◽  
Traffic Jam ◽  
Traffic Lights ◽  
Traffic Light Control

Abstract Intelligent traffic light control system belongs to the field of transportation public safety control. So far, the traffic light control system on the market cannot change the working time of the traffic lights according to the actual traffic flow, which is not conducive to the easing of the traffic flow and easy to cause traffic jams. Therefore, it is necessary to solve the problem of the existing traffic light control system which cannot adjust the working hours of the traffic light according to the actual road conditions, so as to alleviate the traffic jam at the intersection to a certain extent. In this paper, the design of intelligent traffic light control system uses AT89C51 MCU as the core device. The system controls the traffic of different times and different conditions, and it can alleviate traffic jam to a certain extent. This paper analyzes the hardware and software designes of intelligent traffic light control system, and simulates traffic light control by simulation software. The system of this paper is simple in structure, economical and practical, reliable in operation and it can effectively dredge the traffic.

scholarly journals Formation of the Traffic Flow Rate under the Influence of Traffic Flow Concentration in Time at Controlled Intersections in Tyumen, Russian Federation

2021 ◽  
Vol 13 (15) ◽  
pp. 8324
Author(s):  
Viacheslav Morozov ◽  
Sergei Iarkov
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Traffic Congestion ◽  
Traffic Management ◽  
System Analysis ◽  
Motor Vehicle ◽  
Experimental Studies ◽  
Transport Systems ◽  
Experiment Planning ◽  
Traffic Light

Present experience shows that it is impossible to solve the problem of traffic congestion without intelligent transport systems. Traffic management in many cities uses the data of detectors installed at controlled intersections. Further, to assess the traffic situation, the data on the traffic flow rate and its concentration are compared. Latest scientific studies propose a transition from spatial to temporal concentration. Therefore, the purpose of this work is to establish the regularities of the influence of traffic flow concentration in time on traffic flow rate at controlled city intersections. The methodological basis of this study was a systemic approach. Theoretical and experimental studies were based on the existing provisions of system analysis, traffic flow theory, experiment planning, impulses, probabilities, and mathematical statistics. Experimental data were obtained and processed using modern equipment and software: Traficam video detectors, SPECTR traffic light controller, Traficam Data Tool, SPECTR 2.0, AutoCad 2017, and STATISTICA 10. In the course of this study, the authors analyzed the dynamics of changes in the level of motorization, the structure of the motor vehicle fleet, and the dynamics of changes in the number of controlled intersections. As a result of theoretical studies, a hypothesis was put forward that the investigated process is described by a two-factor quadratic multiplicative model. Experimental studies determined the parameters of the developed model depending on the directions of traffic flow, and confirmed its adequacy according to Fisher’s criterion with a probability of at least 0.9. The results obtained can be used to control traffic flows at controlled city intersections.

Effect of pedestrian traffic light on traffic flow accompany with pedestrian crossing

2021 ◽  
pp. 126059
Author(s):  
Yanhong Wang ◽  
Chong Zhang ◽  
Pengbin Ji ◽  
Tianning Si ◽  
Zhenzhen Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Light ◽  
Pedestrian Traffic ◽  
Pedestrian Crossing

Smart Traffic Light System

2021 ◽  
Vol 9 (9) ◽  
pp. 679-686
Author(s):  
Rashi Maheshwari
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Monitoring ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Mathematical Functions ◽  
Light System ◽  
Smart Traffic ◽  
And Control

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

scholarly journals Dynamic Traffic Light Control

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Monitoring ◽  
Intelligent Transport System ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Traffic Management System

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).

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