• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1934-1937
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• 2022

The meaning of crosswalks and traffic lights in modern society has changed a lot as the enforcement of traffic signal violations has been strengthened. In this paper, we present a new next-generation traffic light method using radar and Can-bus communication methods suitable for the new traffic signal enforcement system. This method is a system that prevents accidents by transmitting information on the entry of a person and a car to a traffic light in a place where a person and a car passing through a mutually invisible traffic light cannot be seen. Since this system has only been developed for a month, it may be somewhat lacking in experimentation. However, in just one month, there have been no incidents except for a few people where the system has been installed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.721-722
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• 2017

This paper propose the method of an improved traffic light controller. the proposed improved traffic light controller are more systematic and decrement power consumption than earlier traffic light controller.

• Journal of Korean Society of Transportation
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• v.21 no.6
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• pp.67-73
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• 2003

This study preformed a research about the traffic signal light that is adding supplementary green light to prevent driver's cognitive errors and plan safe driving through improving visual cognitivity of present traffic signal light. The result of comparing the present traffic signal light(three colors, four colors) with the traffic signal light(three colors, four colors) adding supplementary green light through car simulator has a significant difference. This result shows possibility that the traffic signal light adding supplementary green light can contribute in safety driving at a point that the traffic signal light advances a point of braking time when drivers didn't recognize by themselves. The findings in this study ca say that there is the meaning in showing a actual application possibility of this study finding by investigating a action of subjective response the moment compare driver's actual response.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.596-700
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• 1998

Nowadays, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delaytime and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30∼45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electrosensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which doesn't consider vehicle length.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.214-224
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• 2016

This paper proposes an algorithm to effectively detect the traffic lights and recognize the traffic signals using a monocular camera mounted on the front windshield glass of a vehicle in day time. The algorithm consists of three main parts. The first part is to generate the candidates of a traffic light. After conversion of RGB color model into HSI and YCbCr color spaces, the regions considered as a traffic light are detected. For these regions, edge processing is applied to extract the borders of the traffic light. The second part is to divide the candidates into traffic lights and non-traffic lights using Haar-like features and Adaboost algorithm. The third part is to recognize the signals of the traffic light using a template matching. Experimental results show that the proposed algorithm successfully detects the traffic lights and recognizes the traffic signals in real time in a variety of environments.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.48-54
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• 2023

Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.

• Journal of KIISE
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• v.42 no.10
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• pp.1231-1238
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• 2015

Traffic light rules are one among the most common and important safety rules as the directly correlate with the safety of pedestrians. Consequently, an algorithm is required to cause an automated (or semi-automated) vehicle to observe traffic light signals. We present a novel, artificial potential function to guide an automated vehicle through traffic lights. Our function consists of three potential function components representing the three traffic light colors: green, yellow, and red. The traffic light potential function smoothly changes an artificial potential field using the elapsed time for the current light and light conversion. Our traffic light potential function is combined with other potential functions to guide vehicles' movement and constructs the final artificial potential field. Using various simulations, we found or method successfully guided the vehicle to observe traffic lights while behaving like human-controlled cars.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.247-252
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• 2014

Traffic network is composed of passing vehicls, delayed vehicles, traffic situation which is traffic incomes of traffic interfacing system. Traffic green time light is concluded by inside input factor, that is green light cycle, yellow light cycle, led light cycle, which light cycle is sensor inputs. That light cycle is converted to traffic phase composed of passing peoples and delayed vehicles, whose intervals is concluding of traffic network factors composed of consumptiom power factors, delayed time situation, occupying sensor nodes. This is very important sector,because of much poor traffic situation.