• Title/Summary/Keyword: Traffic Light

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Detection of a Light Region Based on Intensity and Saturation and Traffic Light Discrimination by Model Verification (명도와 채도 기반의 점등영역 검출 및 모델 검증에 의한 교통신호등 판별)

  • Kim, Min-Ki
    • Journal of Korea Multimedia Society
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    • v.20 no.11
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    • pp.1729-1740
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    • 2017
  • This paper describes a vision-based method that effectively recognize a traffic light. The method consists of two steps of traffic light detection and discrimination. Many related studies have used color information to detect traffic light, but color information is not robust to the varying illumination environment. This paper proposes a new method of traffic light detection based on intensity and saturation. When a traffic light is turned on, the light region usually shows values with high saturation and high intensity. However, when the light region is oversaturated, the region shows values of low saturation and high intensity. So this study proposes a method to be able to detect a traffic light under these conditions. After detecting a traffic light, it estimates the size of the body region including the traffic light and extracts the body region. The body region is compared with five models which represent specific traffic signals, then the region is discriminated as one of the five models or rejected as none of them. Experimental results show the performance of traffic light detection reporting the precision of 97.2%, the recall of 95.8%, and correct recognition rate of 94.3%. These results shows that the proposed method is effective.

Constructing Effective Smart Crosswalk Traffic Light Mechanism Through Simulation Technique (시뮬레이션 기법을 통한 효율적 스마트 보행신호등 메커니즘 구축)

  • Lee, Hyeonjun;Moon, Soyoung;Kim, R.Youngchul;Son, Hyeonseung
    • KIISE Transactions on Computing Practices
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    • v.22 no.2
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    • pp.113-118
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    • 2016
  • The walking speed of handicapped people generally is slower than that of normal people. So it is difficult for them to cross at crosswalks within the allotted time provided by the traffic light. This problem can be solved by expanding the time of the traffic light. However, if the latency of the traffic light is increased without distinguishing the handicapped among all other pedestrians, the efficiency of traffic signal lights will decrease. In this paper, we propose a smart traffic signal connecting mechanism between the previous pedestrian traffic signal and a pedestrian's device (smartphone). This Smart pedestrian traffic light, through this mechanism, minimizes traffic congestion by providing additional walking time only to the handicapped among pedestrians. This crosswalk traffic light recognizes the handicapped using a technique called Internet of things (IOT). In this paper, we extract the data necessary to build an effective smart crosswalk traffic light mechanism through simulation techniques. We have extracted different kinds of traffic signal times with our virtual simulation environment to verify the efficiency of the smart crosswalk pedestrian traffic light system. This approach can validate the effective delay time of the traffic signal time through a comparison based on number of pedestrians.

Vision based Traffic Light Detection and Recognition Methods for Daytime LED Traffic Light (비전 기반 주간 LED 교통 신호등 인식 및 신호등 패턴 판단에 관한 연구)

  • Kim, Hyun-Koo;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.3
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    • pp.145-150
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    • 2014
  • This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

Traffic Light Recognition Using a Deep Convolutional Neural Network (심층 합성곱 신경망을 이용한 교통신호등 인식)

  • Kim, Min-Ki
    • Journal of Korea Multimedia Society
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    • v.21 no.11
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    • pp.1244-1253
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    • 2018
  • The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

Traffic Light Detection Method in Image Using Geometric Analysis Between Traffic Light and Vision Sensor (교통 신호등과 비전 센서의 위치 관계 분석을 통한 이미지에서 교통 신호등 검출 방법)

  • Choi, Changhwan;Yoo, Kook-Yeol;Park, Yongwan
    • IEMEK Journal of Embedded Systems and Applications
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    • v.10 no.2
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    • pp.101-108
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    • 2015
  • In this paper, a robust traffic light detection method is proposed by using vision sensor and DGPS(Difference Global Positioning System). The conventional vision-based detection methods are very sensitive to illumination change, for instance, low visibility at night time or highly reflection by bright light. To solve these limitations in visual sensor, DGPS is incorporated to determine the location and shape of traffic lights which are available from traffic light database. Furthermore the geometric relationship between traffic light and vision sensor is used to locate the traffic light in the image by using DGPS information. The empirical results show that the proposed method improves by 51% in detection rate for night time with marginal improvement in daytime environment.

Development of LED Traffic Light Lens with snow removing function (제설 기능을 갖는 LED 신호등 렌즈 개발)

  • Lee, Dongeun;Seol, Dongyoul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.4
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    • pp.41-48
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    • 2017
  • It is necessary to develop an LED traffic light lens having a snow removal function capable of clearly providing a traffic signal to the driver even when a traffic light is blurred due to heavy snow and wind in the winter season. This study is focused on the research and development of the traffic light lens in the process of developing the LED traffic light with the snow removal function. In the developed traffic light lens, instead of attaching the film heater, the coated nichrome wire was wound into a coil shape and inserted directly into the groove in the lens. The developed heater system facilitates the insertion of the heating wire with high elasticity into a curved lens and can provide a sufficient heat without deformation of the PC lens. The proposed traffic lights were tested in various external environments and the test results showed that complete snow removal is possible without tunnel effect.

Wireless Traffic Light using Artificial Intelligence

  • Hong, You-Sik;Kim, Chong-Soo;Kim, Chang-Kyun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.251-257
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    • 2003
  • In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic Intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not consider emergency vehicles for safety escort.

Wireless Traffic Signal Light using Fuzzy Rules

  • Hong YouSik;Lu Wei-Ming;Yi JaeYoung;Yi CheonHee
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.365-370
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    • 2004
  • In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not considering emergency vehicles for safety escort.

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Detection and Recognition of Traffic Lights for Unmanned Autonomous Driving (무인 자율주행을 위한 신호등의 검출과 인식)

  • Kim, Jang-Won
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.6
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    • pp.751-756
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    • 2018
  • This research extracted traffic light from input video, recognized colors of traffic light, and suggested traffic light color recognizing algorithm applicable to manless autonomous vehicle or ITS by distinguishing signs. To extract traffic light, suggested algorithm extracted the outline with CEA(Canny Edge Algorithm), and applied HCT(Hough Circle Transform) to recognize colors of traffic light and improve the accuracy. The suggested method was applied to the video of stream acquired on the road. As a result, excellent rate of traffic light recognition was confirmed. Especially, ROI including traffic light in input video was distinguished and computing time could be reduced. In even area similar to traffic light, circle was not extracted or V value is low in HSV space, so it's failed in candidate area. So, accuracy of recognition rate could be improved.

Optimal Traffic Signal Light (최적교통신호등)

  • 홍유식
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.4
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    • pp.181-192
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    • 2003
  • Increased vehicles on the restricted road, the conventional traffic light to losses the function of optimal cycle. The conventional traffic light dose not consider passenger car unit ,offset, and length of traffic intersection. As a result, 30~45% of conventional traffic cycle does not match the present traffic cycle. In this paper, we study the disard vantage of conventional traffic light and improve the vehicle average waiting time in the traffic intersection and vehicle average speed using fuzzy logic. Moreover, it will be able to forecast the optimal traffic information, road under construction and dangerous road using internet.