• Title/Summary/Keyword: Traffic Sign

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Analysis on the Accident Factors of Pedestrian Accident Severity in Roundabout Near School (학교와 인접한 회전교차로 보행자 사고심각도 영향요인 분석)

  • Son, Seul Ki;Park, Byung Ho
    • Journal of the Korean Society of Safety
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    • v.33 no.3
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    • pp.71-76
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    • 2018
  • The purpose of this study is to analyze the factors affecting the roundabout accidents near schools. This study gives particular attentions discussing characteristics by pedestrian accident severity using the ordered logit models. In pursuing the above, 63 roundabouts installed before 2014 are surveyed for modeling. the traffic accident data from 2014 to 2016 are collected from TAAS data set of Road Traffic Authority. Such 35variables explaining the accidents as environment, human, geometries, school and roundabout factor are selected from literature reviews. The main results are as follows. First, the ordered logit models (${\rho}^2$ of 0.272, $x^2$ of 24.723) which is statistically significant have been developed. Second, environment factor variable is analyzed to be day or night ($X_1$ ), human factor variables are evaluated to be driver gender($X_4$), older driver($X_5$), pedestrian gender($X_7$) and children pedestrian($X_8$ ). Third, geometries factor variable are analyzed to be speed limit sign($X_{16}$) and median barrier($X_{21}$), school factor variables are evaluated to be hump-type crosswalk($X_{25}$), CCTV($X_{26}$) and school zone sign($X_{27}$), roundabout factor are analyzed to be roundabout sign($X_{30}$) and number of circulatory roadway lane($X_{32}$). Finally, this study could give some implications to decreasing the accidents severity at roundabout near schools.

Clinical Case Study on Piriformis Syndrome after Traffic Accident (교통사고 후 발생한 이상근 증후군 치험 1례)

  • Yun, Jong-Min;Lee, Jung-Han
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.24 no.5
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    • pp.898-902
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    • 2010
  • This study is performed to report that oriental medical treatment was effective to the patient with piriformis syndrome after traffic accident. The patient was diagnosed as piriformis syndrome by considering clinical symptom, clinical history, physical examination, radiologic study and NCV EMG study. We applied acupuncture, herbal medicine, cupping, Chuna manipulation and exercise to the patient. After treatment, VAS decreased, and physical examination sign was disappeared. This result suggest that oriental medical treatment can be effective to piriformis syndrome.

Intelligence Transportation Safety Information System

  • Hong, YouSik;Park, Chun Kwan;Cho, Seongsoo;Hong, Suck-Joo
    • International Journal of Internet, Broadcasting and Communication
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    • v.6 no.2
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    • pp.20-24
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    • 2014
  • These days the large-scale car accidents have often been occurred by overspeeding in disregard of sharp curve, foggy and freezing regions. This paper has proposed the algorithm to calculate the safety speed in real time that can protect the car accidents under these weather and road conditions using Fuzzy reasoning theory. Under raining and snowing, drivers have to slow down the traffic safety speed by 1/3 of the traffic safety speed indicated on the existing speed sign plate based on their decision. So it is difficult to calculate and then observe the safety speed. This paper has performed the simulation that provides the deivers with the optimal safety speed considering the road and weather conditions in real time to improve these problems. We have proved this method can improve more 25% than the existing one.

An HMM-Based Segmentation Method for Traffic Monitoring (HMM 분할에 기반한 교통모니터링)

  • 남기환;배철수;정주병;나상동
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.587-590
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    • 2004
  • In this paper proposed a HMM(Hidden Martov Model)-based segmentation method which is able to model shadows as well as foreground and background regions. Shadow of moving objects often obstruct visual tracking. We propose an HMM-based segmentation method which classifies in real time oath objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results

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Traffic Sign Recognition using SVM and Decision Tree for Poor Driving Environment (SVM과 의사결정트리를 이용한 열악한 환경에서의 교통표지판 인식 알고리즘)

  • Jo, Young-Bae;Na, Won-Seob;Eom, Sung-Je;Jeong, Yong-Jin
    • Journal of IKEEE
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    • v.18 no.4
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    • pp.485-494
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    • 2014
  • Traffic Sign Recognition(TSR) is an important element in an Advanced Driver Assistance System(ADAS). However, many studies related to TSR approaches only in normal daytime environment because a sign's unique color doesn't appear in poor environment such as night time, snow, rain or fog. In this paper, we propose a new TSR algorithm based on machine learning for daytime as well as poor environment. In poor environment, traditional methods which use RGB color region doesn't show good performance. So we extracted sign characteristics using HoG extraction, and detected signs using a Support Vector Machine(SVM). The detected sign is recognized by a decision tree based on 25 reference points in a Normalized RGB system. The detection rate of the proposed system is 96.4% and the recognition rate is 94% when applied in poor environment. The testing was performed on an Intel i5 processor at 3.4 GHz using Full HD resolution images. As a result, the proposed algorithm shows that machine learning based detection and recognition methods can efficiently be used for TSR algorithm even in poor driving environment.

The Road Speed Sign Board Recognition, Steering Angle and Speed Control Methodology based on Double Vision Sensors and Deep Learning (2개의 비전 센서 및 딥 러닝을 이용한 도로 속도 표지판 인식, 자동차 조향 및 속도제어 방법론)

  • Kim, In-Sung;Seo, Jin-Woo;Ha, Dae-Wan;Ko, Yun-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.4
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    • pp.699-708
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    • 2021
  • In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

School Zone Safety Improvement Using Smart Bollard (Smart Bollard를 이용한 어린이보호구역에서의 안전성 제고에 관한 연구)

  • Kim, Hoe Kyoung;Lim, Jae Moon;Sul, Jae Hoon;Oh, Yun Pyo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.1
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    • pp.251-259
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    • 2013
  • This paper is aimed to introduce to a moving bollard (i.e., smart bollard) to improve the pedestrian safety along the crosswalk in the school zone as a means to physically separate pedestrians and approaching vehicles, to propose the appropriate criteria for its installation and implementation from the traffic engineering perspective, and to evaluate its effectiveness with the microscopic simulation model. The simulation results indicate that implementing the smart bollard results in the decrease of average approaching speed and traffic throughput and the most critical factors affecting its effectiveness are yellow time of the traffic signal directly associated with the location of the advance warning sign and its operation time, 5~6 seconds and 2~3 seconds, respectively.

Use of a Driving Simulator to Determine Optimum VMS Locations for Freeway Off-ramp Traffic Diversion (Driving Simulator를 이용한 유출지점 경로안내용 VMS 적정 설치 위치 결정에 관한 연구)

  • Oh, Cheol;Kim, Tae-Hyung;Lee, Jae-Joon;Lee, Soo-Beom;Lee, Chung-Won
    • Journal of Korean Society of Transportation
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    • v.26 no.1
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    • pp.155-164
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    • 2008
  • Variable Message Signs (VMS) is one of the major components for Intelligent Transport Systems (ITS) services that provides real-time traffic and incident information to drivers. The objective of this research was to develop a method determining the optimal location of VMS considering safety and driving characteristics of various drivers. A driving simulator was utilized to evaluate how drivers can safely exit to off-ramp depending on various VMS locations while information relating route diversion was provided. The binary logistic regression and factor analysis were applied in developing a probability model that predicts the success of safe off-ramp exiting. Based on the developed probability model, a method to estimate the spacing between VMS and off-ramp is suggested. It is expected that the products of this study would be utilized as a tool in determining VMS locations for ITS planners and designers.

Constructing the Models Estimated for Speed Variation on the Merge Section in the Freeway (고속도로의 합류구간내 속도변화 추정모형 구축에 관한 연구)

  • 신광식;김태곤
    • Journal of Korean Port Research
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    • v.13 no.1
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    • pp.113-122
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    • 1999
  • Congestion and traffic accidents occur on the merge and diverge sections in the interchange of the freeway. Studies have been conducted to reduce the traffic delay and accidents on the merge section in the freeway since 1960s. but a study was not conducted to estimate the speed variation on the merge section construct models estimated for the speed variation and suggest the appropriate measures. The purpose of this study was to identify the traffic flow characteristics on the merge section in the freeway construct the models estimated for the speed variation on the merge section in the freeway and finally establish the appropriate measure for reduction of traffic delay and accidents on the merge section in the freeway. The following results were obtained: I) Speed variations in the urban freeway appeared to be about 3.2mph, 6.5mph and 7.4mph based on the morning peak period, afternoon peak period and 24-hours period but those in the suburban freeway appeared to be about 8.0mph, 11.1mph and 10.1mph based on the same periods respectively. So different speed reduction signs need be installed to reduce delay and accidents on the merge section in the freeway based on the areas and periods as the freeway traffic management system(FTMS). ii) These models estimated for speed variation need to be studied with the changeable message sign(CMS) technique based on the real-time data so that the traffic flow could be maximized and the traffic delay and accidents be on the merge section in the freeway as more efficient freeway traffic management system(FTMS) in the near future.

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The Development of Customer Satisfaction Model by Traffic Information Provision Media (교통정보 제공 매체별 이용자 만족도 모형 개발)

  • Hong, Ji-Yeon;Lee, Su-Beom;Im, Jun-Beom;Kim, Jang-Uk;Gang, Won-Ui
    • Journal of Korean Society of Transportation
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    • v.28 no.3
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    • pp.109-117
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    • 2010
  • The purpose of advanced traffic information system(ATIS) is to help drivers save time and energy in getting to their destinations by providing traffic information through variable message sign(VMS), internet, traffic broadcasting and mobile phones. ATIS does not just provide drivers with benefits in terms of time and energy, but it provides them with psychological benefit as well, i.e., the drivers can relieve their anxiety by getting provided with traffic information. In this study, the efficiency of traffic information system is evaluated and degree of satisfaction of drivers with the system is analyzed by building satisfaction models of various media of traffic information. Each medium has different factors for satisfaction and each factor has different degree of influence, but in general, the efficiency of traffic information in helping drivers choose routes and in providing drivers with peace of mind is considered to have the highest influence on satisfaction of drivers with the system.