• Title/Summary/Keyword: Traffic information

Search Result 7,062, Processing Time 0.032 seconds

An Analysis of Safety Impacts of Variable Message Signage as Functions of Road Curve Radius (도로곡선반경에 따른 가변전광표지의 교통안전효과 분석)

  • Lee, Sang Hyuk;Cho, Hye-Jin
    • International Journal of Highway Engineering
    • /
    • v.17 no.5
    • /
    • pp.47-56
    • /
    • 2015
  • PURPOSES: The purpose of this study is to estimate the impact of variable message signage (VMS) on traffic safety as a function of road curve radius using statistical methods. METHODS: In order to analyze the impact of VMS installations on traffic safety, travel speed, lateral distance, and geometric data relating to road curvature in each study area was acquired and analyzed for the impact of providing VMS information on driver performance and traffic safety using statistical methods including student t-test, Mann-Whitney test, and the Anderson-Darling test for estimating traffic safety hazard zone in each lane. RESULTS: As a result of analyzing driver performance characteristics before and after providing VMS information, it was determined that by providing VMS information, mean travel speed is deceased and vehicles are driven with increased precision, following the centerline in the first and second lanes. Also the results of analyzing traffic safety impacts of VMS indicate that traffic safety performance factors in the first lane of the Gapyeong section can, on average, increase in the left and right side of the lane by 19.22% and 68.98%, respectively, and in the case of the second lane, safety impacts, on average, can increase in both sides by 100%. For the Hongcheon section, traffic safety impacts in the first lane, on average, can increase along the left and right sides of the lane by 32.31% and 47.18%, and within the second lane, traffic safety can be increased along the left and right side of the lane by 10.97% and -0.01%, respectively. CONCLUSIONS: Based on the results of this study, the impact on traffic safety obtained by providing VMS information for road sections with smaller curve radii is greater than can be obtained for road sections with larger curve radii.

Service Identification Method for Encrypted Traffic Based on SSL/TLS (SSL/TLS 기반 암호화 트래픽의 서비스 식별 방법)

  • Kim, Sung-Min;Park, Jun-Sang;Yoon, Sung-Ho;Kim, Jong-Hyun;Choi, Sun-Oh;Kim, Myung-Sup
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.40 no.11
    • /
    • pp.2160-2168
    • /
    • 2015
  • The SSL/TLS, one of the most popular encryption protocol, was developed as a solution of various network security problem while the network traffic has become complex and diverse. But the SSL/TLS traffic has been identified as its protocol name, not its used services, which is required for the effective network traffic management. This paper proposes a new method to generate service signatures automatically from SSL/TLS payload data and to classify network traffic in accordance with their application services. We utilize the certificate publication information field in the certificate exchanging record of SSL/TLS traffic for the service signatures, which occurs when SSL/TLS performs Handshaking before encrypt transmission. We proved the performance and feasibility of the proposed method by experimental result that classify about 95% SSL/TLS traffic with 95% accuracy for every SSL/TLS services.

Advanced Freeway Traffic Safety Warning Information System based on Surrogate Safety Measures (SSM): Information Processing Methods (Surrogate Safety Measures(SSM)기반 고속도로 교통안전 경고정보 처리 및 가공기법)

  • O, Cheol;O, Ju-Taek;Song, Tae-Jin;Park, Jae-Hong;Kim, Tae-Jin
    • Journal of Korean Society of Transportation
    • /
    • v.27 no.3
    • /
    • pp.59-70
    • /
    • 2009
  • This study presents a novel traffic information system which is capable of detecting unsafe traffic events leading to accident occurrence and providing warning information to drivers for safer driving. Unsafe traffic events are captured by a vehicle image processing-based detection system in real time. Surrogate safety measures (SSM) representing quantitative accident potentials were derived, and further utilized to develop a data processing algorithm and analysis techniques in the proposed system. This study also defined 'emergency warning area' and 'general warning area' for more effective provision of warning information. In addition, methodologies for determining thresholds to trigger warning information were presented. Technical issues and further studies to fully exploit the benefits of the proposed system were discussed. It is expected that the proposed system would be effective for better management of traffic flow to prevent traffic accidents on freeways.

An Analysis on Service Usage of Traffic Information on the Expressway (고속도로 교통정보 서비스에 대한 이용실태 분석)

  • Oh, Dong-Seob;Oh, Young-Tae;Jo, Soon-Gee;Hong, Eun-Joo
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.8 no.5
    • /
    • pp.12-25
    • /
    • 2009
  • The purpose of this study is to identify and analyze drivers' attitude related to usage of traffic information and traffic management service. A sample survey on Seohaeanseon Expressway(15), Gyeongbu Experssway(1), Youngdong Expressway(50) was conducted to analyze drivers' attitude ; sample size is 304 with 95% of confidence level and ${\pm}3.6%$ of sampling error. The analysis lists of drivers' attitude are usage of traffic information, awareness about information dissemination devices, and awareness about traffic control information related to LCS or RWIS. The results of this study is that drivers want pre-trip information, voice-based Hi-pass OBU, and fast incident management. According to the IPA, KEC's main consideration is a traffic flow improvement.

  • PDF

A Study on Developing Traffic Data Converting Algorithm for FM DARC (FM DARC용 교통정보 변환알고리즘 개발)

  • Lee, Bong-Gyu
    • Journal of Korea Spatial Information System Society
    • /
    • v.2 no.2 s.4
    • /
    • pp.39-48
    • /
    • 2000
  • The purpose of this study is to develop a converting algorithm for providing real-time traffic information through the FM DARC(DAta Radio Channel). The converting algorithm based on the GIS node-link system enables raw traffic data to be a standard traffic information. The standard traffic information in data quality, quantity and format is an essential to construct the FM DARC traffic information system effectively. We have developed the algorithm and applied it to the FM DARC system. After introducing FM DARC briefly, this paper presents GIS DB, the converting algorithm and the client/server FM DARC system.

  • PDF

Evaluating GHG Emissions Reduced by Real-time Traffic Information in Gasoline Vehicle (실시간교통정보 이용에 따른 가솔린차량의 온실가스 저감효과 평가)

  • Kim, Jun-Hyung;Um, Jung-Sup
    • Journal of Korean Society for Atmospheric Environment
    • /
    • v.27 no.4
    • /
    • pp.443-453
    • /
    • 2011
  • Real-time Traffic Information Service could play a key role in reducing incomplete combustion time remarkably since it can provide traffic information in real-time basis. Emission characteristics of test engines were studied in terms of travel distance and speed. The present study focused on a north district in Daegu, 12 km. The driving for the emission test was done at 8AM, 3PM, 7PM which represents various traffic conditions. The reduced emissions of Greenhouse Gases (GHG) have been measured for a travel distance running at different loads (conventional shortest route and Real-time Traffic Information) and GHG ($CO_2$, $CH_4$, $N_2O$) are all inventoried and calculated in terms of existing emission factors. The emission of GHG has been shown to reduce linearly with travel distance: $CO_2$ (9.15%), $CH_4$ (18.43%), $N_2O$(18.62%).

Power Saving Scheme by Distinguishing Traffic Patterns for Event-Driven IoT Applications

  • Luan, Shenji;Bao, Jianrong;Liu, Chao;Li, Jie;Zhu, Deqing
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.13 no.3
    • /
    • pp.1123-1140
    • /
    • 2019
  • Many Internet of Things (IoT) applications involving bursty traffic have emerged recently with event detection. A power management scheme qualified for uplink bursty traffic (PM-UBT) is proposed by distinguishing between bursty and general uplink traffic patterns in the IEEE 802.11 standard to balance energy consumption and uplink latency, especially for stations with limited power and constrained buffer size. The proposed PM-UBT allows a station to transmit an uplink bursty frame immediately regardless of the state. Only when the sleep timer expires can the station send uplink general traffic and receive all downlink frames from the access point. The optimization problem (OP) for PM-UBT is power consumption minimization under a constrained buffer size at the station. This OP can be solved effectively by the bisection method, which demonstrates a performance similar to that of exhaustive search but with less computational complexity. Simulation results show that when the frame arrival rate in a station is between 5 and 100 frame/second, PM-UBT can save approximately 5 mW to 30 mW of power compared with an existing power management scheme. Therefore, the proposed power management strategy can be used efficiently for delay-intolerant uplink traffic in event-driven IoT applications, such as health status monitoring and environmental surveillance.

A Real Time Traffic Flow Model Based on Deep Learning

  • Zhang, Shuai;Pei, Cai Y.;Liu, Wen Y.
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.16 no.8
    • /
    • pp.2473-2489
    • /
    • 2022
  • Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

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
    • /
    • v.20 no.11
    • /
    • pp.1729-1740
    • /
    • 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.