• Title/Summary/Keyword: intelligent traffic system

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Intelligent Traffic Forecasting System using Fuzzy Logic (Fuzzy 논리를 이용한 지능형 교통 혼잡도 예측 시스템 설계)

  • 김종국;김종원;조현찬;서화일;이재협;백승철
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.99-102
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    • 2001
  • It has well known that the congestion of traffic and it's distribution. There are very important problems in the traffic control systems. In this paper, we will purpose an ITFS(Intelligent Traffic Forecasting System) which can determine the car classes and transport them to ITS(Intelligent Traffic control System). The system will be used the Inductive Loop Detector(ILD)and the Fuzzy logic and shown the effectiveness by the computer simulation.

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Design and Implementation of Advanced Traffic Monitoring System based on Integration of Data Stream Management System and Spatial DBMS

  • Xia, Ying;Gan, Hongmei;Kim, Gyoung-Bae
    • Journal of Korea Spatial Information System Society
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    • v.11 no.2
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    • pp.162-169
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    • 2009
  • The real-time traffic data is generated continuous and unbounded stream data type while intelligent transport system (ITS) needs to provide various and high quality services by combining with spatial information. Traditional database techniques in ITS has shortage for processing dynamic real-time stream data and static spatial data simultaneously. In this paper, we design and implement an advanced traffic monitoring system (ATMS) with the integration of existed data stream management system (DSMS) and spatial DBMS using IntraMap. Besides, the developed ATMS can deal with the stream data of DSMS, the trajectory data of relational DBMS, and the spatial data of SDBMS concurrently. The implemented ATMS supports historical and one time query, continuous query and combined query. Application programmer can develop various intelligent services such as moving trajectory tracking, k-nearest neighbor (KNN) query and dynamic intelligent navigation by using components of the ATMS.

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A Study on the Verification of Traffic Flow and Traffic Accident Cognitive Function for Road Traffic Situation Cognitive System

  • Am-suk, Oh
    • Journal of information and communication convergence engineering
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    • v.20 no.4
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    • pp.273-279
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    • 2022
  • Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

An Architecture Design and Implementation of Stateful Traffic Generation for Cyber Warfare Training (사이버전 훈련을 위한 상태 저장 트래픽 발생 Architecture 설계 및 구현)

  • Hong, Suyoun;Kim, Kwangsoo;Kim, Taekyu
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.3
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    • pp.267-276
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    • 2020
  • Threats targeting cyberspace are becoming more intelligent and increasing day by day. To cope with such cyber threats, it is essential to improve the coping ability of system security officers. In this paper, we propose a stateful traffic generator that provide network background traffic for cyber warfare training. The proposed architecture is designed for generating traffic similar to real system traffic, so the trainee can perform more realistic training.

Applying the IoT platform and green wave theory to control intelligent traffic lights system for urban areas in Vietnam

  • Phan, Cao Tho;Pham, Duy Duong;Tran, Hoang Vu;Tran, Trung Viet;Huu, Phat Nguyen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.34-52
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    • 2019
  • This paper proposes an intelligent system performing an application with assistance of an Internet of Things (IoT) platform to control a traffic lights system. In our proposed systems, the traffic lights can be remotely controlled through the Internet. Based on IoT platform, the traffic conditions at different intersections of roads are collected and the traffic lights are controlled in a central manner. For the software part, the algorithm is designed based on the green wave theory to maximize the green bandwidth of arterial roads while addressing a challenging issue: the rapid changes of parameters including cycle time, splits, offset, non-fixed vehicles' velocities and traffic flow along arterial roads. The issue typically happens at some areas where the transportation system is not well organized like in Vietnam. For the hardware part, PLC S7-1200 are placed at the intersections for two purposes: to control traffic lights and to collect the parameters and transmit to a host machine at the operation center. For the communication part, the TCP/IP protocol can be done using a Profinet port embedded in the PLC. Some graphical user interface captures are also presented to illustrate the operation of our proposed system.

Development of Traffic Congestion Prediction Module Using Vehicle Detection System for Intelligent Transportation System (ITS를 위한 차량검지시스템을 기반으로 한 교통 정체 예측 모듈 개발)

  • Sin, Won-Sik;Oh, Se-Do;Kim, Young-Jin
    • IE interfaces
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    • v.23 no.4
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    • pp.349-356
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    • 2010
  • The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

The Study on Sensor based Service Model of Traffic Facilities (센서 기반의 교통시설물 서비스 발전방향에 관한 연구)

  • Lee, Yong-Joo;Kim, Jy-So;Chang, Hoon;Jeong, Jin-Seok
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.4
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    • pp.415-421
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    • 2008
  • The purpose of this study is to provide a sensor based service model for traffic facilities in u-City through analysing the present condition of urban infrastructure, especially traffic facilities management. In order to achieve this purpose, we did a comparative analysis of internal and external situation of ITS(Intelligent Transport System) and classified service for traffic facilities to 3 categories, namely traffic flow management, traffic information offering, formation of road structure. Also, we examined technological trend of USN(Ubiquitous Sensor Network). Through this process, we present a sensor based service model of traffic facilities for building sustainable road environment.

Reinforcement Learning-Based Adaptive Traffic Signal Control considering Vehicles and Pedestrians in Intersection (차량과 보행자를 고려한 강화학습 기반 적응형 교차로 신호제어 연구)

  • Jong-Min Kim;Sun-Yong Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.143-148
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    • 2024
  • Traffic congestion has caused issues in various forms such as the environment and economy. Recently, an intelligent transport system (ITS) using artificial intelligence (AI) has been focused so as to alleviate the traffic congestion problem. In this paper, we propose a reinforcement learning-based traffic signal control algorithm that can smooth the flow of traffic while reducing discomfort levels of drivers and pedestrians. By applying the proposed algorithm, it was confirmed that the discomfort levels of drivers and pedestrians can be significantly reduced compared to the existing fixed signal control system, and that the performance gap increases as the number of roads at the intersection increases.

Improvement of Information Connection System among Traffic Information Centers (교통정보센터 간 정보 연계체계 개선방안)

  • Lim, Sung Han
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.13 no.2
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    • pp.34-41
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    • 2014
  • The purpose of this study is to present the improvement of connection system between traffic information centers for reliable traffic information service. We recognized traffic information error caused by too much time in conjunction between traffic information centers, lack of reliability of traffic information caused by absence of generation time and generation institution of traffic information. We presented minimization methods of connection time, improvement methods of reliability of traffic information and development methods of connection state management system.