scholarly journals Recent development of smart traffic lights

2021 ◽  
Vol 10 (1) ◽  
pp. 224
Author(s):  
A’isya Nur Aulia Yusuf ◽  
Ajib Setyo Arifin ◽  
Fitri Yuli Zulkifli
Keyword(s):  
Traffic Flow ◽  
Time Allocation ◽  
Traffic Density ◽  
Light Cycle ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
Smart Traffic ◽  
Very High ◽  
Signal Time

<span id="docs-internal-guid-288f4dcc-7fff-1e8c-0350-5032593b6e4f"><span>Increased traffic flow causes congestion, especially in large cities. Even though congestion is not unusual, traffic jams still result in very high economic and social losses. Several factors cause congestion, one of which is traffic lights. Therefore, a mechanism is needed so that traffic lights can intelligently and adaptively manage signal time allocation according to traffic flow conditions. A traffic light with this type of mechanism is known as a smart traffic light. Smart traffic light cycle settings can be grouped based on the traffic density, scenarios for emergency vehicles, and the interests of pedestrians. This paper analyzes the methods and technologies used in the development of smart traffic light technology from the perspective of these three situations as well as the development of smart traffic light technology in the future.</span></span>

scholarly journals Optimization of Traffic Flow On KS Tubun Street using Greenberg Model

2019 ◽  
Vol 8 (2S7) ◽  
pp. 83-86
Keyword(s):  
Traffic Flow ◽  
Red Light ◽  
Green Light ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
The Road ◽  
Road Users ◽  
Time Parameters

KS Tubun Street is a street in Bogor, which has a fairly high vehicle volume and become one of a high-traffic jam area. This is caused by KS Tubun Street is the main road for road users from Jakarta and Bogor. Traffic jam problem that occurs due to the confluence interchange of traffic flow and traffic lights settings that are not proportional to the volume of vehicles across the road. Optimization of traffic flow at KS Tubun Street performed by the stages of forming a model of traffic flow, determining the density and velocity of the vehicle is based on the Greenberg model, and determining the length of the traffic lights to avoid a buildup of vehicles. The result is a traffic flow model with distance and time parameters. The density of vehicles that occurs on the streets of KS. Tubun street based on the Greenberg model between 180 to 240 unit car of passanger (ucp) with the average velocity of vehicles 15 to 19.5 km per hour. The density of vehicles on KS. Tubun street can be break down by increasing time. Traffic light cycle time can be reduced for 8 seconds with the red light glowing time is 80 seconds and the green light glowing time is 62 seconds.

scholarly journals A real-time system for vehicle detection with shadow removal and vehicle classification based on vehicle features at urban roads

2020 ◽  
Vol 11 (4) ◽  
pp. 2091
Author(s):  
Issan Atouf ◽  
Wahban Yahya Al Okaishi ◽  
Abdelmoghit Zaaran ◽  
Ibtissam Slimani ◽  
Mohamed Benrabh
Keyword(s):  
Traffic Flow ◽  
Urban Areas ◽  
Vehicle Detection ◽  
Vehicle Classification ◽  
Traffic Density ◽  
Light Cycle ◽  
Specific Class ◽  
Traffic Light ◽  
Real Time System ◽  
Moving Vehicles

Monitoring traffic in urban areas is an important task for intelligent transport applications to alleviate the traffic problems like traffic jams and long trip times. The traffic flow in urban areas is more complicated than the traffic flow in highway, due to the slow movement of vehicles and crowded traffic flows in urban areas. In this paper, a vehicle detection and classification system at intersections is proposed. The system consists of three main phases: vehicle detection, vehicle tracking and vehicle classification. In the vehicle detection, the background subtraction is utilized to detect the moving vehicles by employing mixture of Gaussians (MoGs) algorithm, and then the removal shadow algorithm is developed to improve the detection phase and eliminate the undesired detected region (shadows). After the vehicle detection phase, the vehicles are tracked until they reach the classification line. Then the vehicle dimensions are utilized to classify the vehicles into three classes (cars, bikes, and trucks). In this system, there are three counters; one counter for each class. When the vehicle is classified to a specific class, the class counter is incremented by one. The counting results can be used to estimate the traffic density at intersections, and adjust the timing of traffic light for the next light cycle. The system is applied to videos obtained by stationary cameras. The results obtained demonstrate the robustness and accuracy of the proposed system.

scholarly journals Development and Designing Smart Traffic Light with Xbee Pro

2018 ◽  
Vol 215 ◽  
pp. 01009
Author(s):  
Alfith Alfith ◽  
Kartiria Kartiria
Keyword(s):  
Green Light ◽  
The Other ◽  
Traffic Density ◽  
Main Function ◽  
Traffic Light ◽  
Traffic Lights ◽  
Road Users ◽  
Fire Engine ◽  
Smart Traffic ◽  
Wireless Module

The main function of the highway are used as a means to facilitate transportation, but today is often challenging due to all road users wanting more quickly reach its destination and precede each other. On the other hand, there is also a special car or entourage effect on traffic density, which in turn impact on congestion. To cope with this is actually the duty of the Traffic Police is not every day got in the way to manage traffic and will not be able to count the number of passing vehicles. To direct the traffic at any place such as a T-junction, an intersection, or intersection five solid pace of the traffic, the necessary traffic arrangements multifunctional tool called Smart Traffic Light. Called smart because the traffic light is deemed able to overcome three problems, such detect traffic density which affects the green light sensor uses the object infrared, able to detect the presence of specific signal from cars special like ambulance or fire engine or police or the like are automatically will change traffic lights red to green light using the XBee wireless module Pro and GPS, and seeks the traffic lights stay lit even though the supply of PLN extinguished using a spare battery. The system is capable of regulating the rate of traffic by arranging alternately road vehicle that passes a certain spot every day for nearly 24 hours a day and on these tools need to pair every day.

scholarly journals Traffic Light Cycle Configuration of Single Intersection Based on Modified Q-Learning

2019 ◽  
Vol 9 (21) ◽  
pp. 4558 ◽  
Author(s):  
Hung-Chi Chu ◽  
Yi-Xiang Liao ◽  
Lin-huang Chang ◽  
Yen-Hsi Lee
Keyword(s):  
Traffic Congestion ◽  
Exhaustive Search ◽  
Urban Traffic ◽  
Light Cycle ◽  
Traffic Light ◽  
Large Cities ◽  
Q Learning ◽  
Traffic Lights ◽  
Vehicle Delay ◽  
Processing Steps

In recent years, within large cities with a high population density, traffic congestion has become more and more serious, resulting in increased emissions of vehicles and reducing the efficiency of urban operations. Many factors have caused traffic congestion, such as insufficient road capacity, high vehicle density, poor urban traffic planning and inconsistent traffic light cycle configuration. Among these factors, the problems of traffic light cycle configuration are the focal points of this paper. If traffic lights can adjust the cycle dynamically with traffic data, it will reduce degrees of traffic congestion significantly. Therefore, a modified mechanism based on Q-Learning to optimize traffic light cycle configuration is proposed to obtain lower average vehicle delay time, while keeping significantly fewer processing steps. The experimental results will show that the number of processing steps of this proposed mechanism is 11.76 times fewer than that of the exhaustive search scheme, and also that the average vehicle delay is only slightly lower than that of the exhaustive search scheme by 5.4%. Therefore the proposed modified Q-learning mechanism will be capable of reducing the degrees of traffic congestions effectively by minimizing processing steps.

scholarly journals An Analysis of A Three-Phase Versus A Four-Phase Traffic Lights Regulation for A Four-Leg Intersection

2020 ◽  
Vol 26 (2) ◽  
pp. 192-201
Author(s):  
Sri Redjeki Pudjaprasetya ◽  
Dear Michiko Noor
Keyword(s):  
Traffic Management ◽  
Traffic Density ◽  
Traffic Light ◽  
Traffic Lights ◽  
Characteristic Lines ◽  
Three Phase ◽  
Light Management ◽  
Phase Regulation ◽  
Parameter Values

Traffic management of intersections is an important factor that can determine traffic density at the intersection, as well as its surrounding. Long traffic queues we encounter in daily life, were often caused by ineffectiveness of traffic lights management of the cross sections.In this article, an analytic study of traffic light management of a four-leg intersection, based on the kinematic LWR model, was presented. Comparison was based on observing the end of queues over three cycles of red-green lights, under the assumption of a constant traffic flux. On every leg of the intersection, the end of the queues were obtained from characteristic lines of the shock waves.From these observations, the three phase regulation was preferred over the four-phase one. Finally, a case study of Taman Sari - Baltos intersection located in Bandung City, Indonesia, was discussed. Parameter values used in these simulations were obtained from direct observation. 

scholarly journals Application of support vector machine in a traffic lights control

2020 ◽  
Vol 14 ◽  
pp. 37-42
Author(s):  
Artur Całuch ◽  
Adam Cieślikowski ◽  
Małgorzata Plechawska-Wójcik
Keyword(s):  
Support Vector Machine ◽  
Cycle Length ◽  
Support Vector ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Lights ◽  
Using Data

This article presents the process of adapting support vector machine model’s parameters used for studying the effect of traffic light cycle length parameter’s value on traffic quality. The survey is carried out using data collected during running simulations in author’s traffic simulator. The article shows results of searching for optimum traffic light cycle length parameter’s value.

scholarly journals Developing Hybrid Simulation Model to Improve Road Traffic Management

2020 ◽  
Vol 4 (01) ◽  
pp. 56-65
Author(s):  
Hayati Mukti Asih
Keyword(s):  
Simulation Model ◽  
Urban Areas ◽  
Traffic Management ◽  
Road Traffic ◽  
Hybrid Simulation ◽  
Simulation Method ◽  
Vital Role ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Lights

Yogyakarta has increasing trends in the number of vehicles and consequently intensifying the traffic volume and will effect to higher emission and air pollution. Traffic lights duration plays a vital role in congestion mitigation in the critical intersections of urban areas. This study has objective to minimize the number of vehicles waiting in line by developing the hybrid simulation method. First of all, the MKJI and Webster method were calculated to determine the green traffic light. Then, the simulation model was developed to evaluate the number of vehicles waiting in line according to different duration of green traffic lights from MKJI and Webster method. A case study will then be provided in Pelemgurih intersection located in Yogyakarta, Indonesia for demonstrating the applicability of the developed method. The result shows that the duration of green traffic lights calculated by Webster method provides lower number of vehicles waiting in line. It is due to the short duration of green traffic light resulted by Webster method so that the traffic light cycle becomes shorter and it effects the number of vehicles waiting in line which is lower than MKJI method. The results obtained can help the generating desired decision alternatives that will important for Department of Transportation, Indonesia to enhance the road traffic management with low number of vehicles waiting in line.

scholarly journals Characteristics of Traffic Flows at Kuda Mati non-traffic light Intersection in Workhour and Holidays

2018 ◽  
Vol 73 ◽  
pp. 08030
Author(s):  
F. Betaubun Herbin
Keyword(s):  
Traffic Flow ◽  
Movement Pattern ◽  
Survey Method ◽  
Traffic Flows ◽  
Traffic Light ◽  
City Center ◽  
Work Time ◽  
Traffic Lights ◽  
Economic Support ◽  
The City

Characteristics of traffic flow needs to be revealed to describe the traffic flow that occurred at the research location. One of the patterns of traffic flow movement of Merauke Regency that is important enough to be observed is the movement pattern that occurs at Kuda Mati Non-traffic lights Intersection. This intersection is one of the access for economic support of Merauke Regency. The intersection connects the city center to the production centers and is used by the community to perform activities in meeting their needs such as working and meeting the needs of clothing, food and shelter. This fulfillment activity is usually differentiated according to work time and holiday time. The method used is survey method to describe the characteristics of traffic flow at the intersection. Data analysis applied MKJI 1997. The results show that peak hour traffic flow occurs at 17.00 - 18.00 on holiday 803 smp / hour, while for working time the traffic flow is evenly distributed with maximum vehicle volume occur at 12:00 to 13:00 which amounted to 471 smp / hour.

Researching the Information of Transmission Technology Based on Traffic Lights

2014 ◽  
Vol 644-650 ◽  
pp. 4538-4541
Author(s):  
Qiang Li ◽  
Xin Rui Zhang
Keyword(s):  
Visible Light ◽  
Image Recognition ◽  
Communication Technology ◽  
High Speed ◽  
Visible Light Communication ◽  
Qr Code ◽  
Visible Light Communications ◽  
Traffic Light ◽  
Traffic Lights ◽  
Very High

This design is based on Visible Light Communication Technology, to achieve outdoor visible light communications and image recognition etc. through traffic lights. It will play a role on promoting the utilization of traffic lights. The system uses a LED dot matrix to imitate the traffic light, loading QR Code information on the LED dot matrix and then transporting it in a very high-speed flashing. In receiving terminal, first, webcam OV7670 collects information which from the LED dot matrix, then conveys the picture to FPGA, which is the processor. FPGA will handle the picture by gray scale processing, medium filtering and binary processing at last. Thus, the picture from the LED dot matrix will change to ‘0’ and ‘1’ in binary area. Secondly, as there’s a relationship between LED dot matrix and webcam pixels, we can count how many pixels represent one LED. Finally, we can decode the QR Code based on its own style, and display the final result on the TFT screen.

scholarly journals Designing a Smart Traffic Light Algorithm (HMS) Based on Modified Round Robin Algorithm

2017 ◽  
Vol 2 (1) ◽  
pp. 27-30
Author(s):  
Hozan Khalid Hamarashid ◽  
Miran Hama Rahim Saeed ◽  
Soran Saeed
Keyword(s):  
Traffic Congestion ◽  
Fixed Time ◽  
Traffic Load ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
Traffic System ◽  
Light System ◽  
Smart Traffic ◽  
Fixed System

Nowadays, traffic light system is very important to avoid car crashes and arrange traffic load. In the Sulaimani City / Iraq, there are many traffic problems such as traffic congestion or traffic jam and the amount of time provided manually to the traffic light system. This is the main difficulty that we try to solve. The traffic lights exist but still do not manage traffic congestion due to the fixed time provided for each lane regardless of their different load. Therefore, we are proposing to change the traditional traffic system to smart traffic system (adaptive system). This paper Focuses on the existing system (fixed system), then propose the adaptive one. The main crucial side effects of the existing system are:   Emergency cases: congested traffics might block the way of emergencies for instance ambulance, which transports people to the hospital Wasting time of people generally and specially Delays, which lead people to not to be punctual, this means people arrive late to the work  Wasting more fuels as staying more in the traffics, which affects the environment by increasing pollution.

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