• Title/Summary/Keyword: Intelligent transportation systems

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Railway strategies for introducing intelligent transportation system (철도분야 지능형교통체계 도입 전략)

  • Lee, Jun;Moon, Dae-Sub;Eom, Jin-Ki;Kim, Dong-Hee;Jin, Il-Kyoung
    • Proceedings of the KSR Conference
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    • 2011.05a
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    • pp.1544-1549
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    • 2011
  • Transportation Efficiency Act of 2009 System National Integrated Transportation System Efficiency Act and the revised Road Traffic in the center of the Intelligent Transportation Systems rail, sea and air transport sector is expanding in various areas to promote business and Industry is planning to. Accordingly, the introduction of Intelligent Transportation Systems Outlook and Direction of the railway sector and to provide a comprehensive introduction of Intelligent Transportation Systems rail sector has raised the need. In this paper, the introduction of Intelligent Transportation Systems rail sector strategy is presented as follows. First, the rail users a convenient rail-centric information system used. Second, the reliability and value-added operating system built for the creation of high-tech rail. Third, crime and accidents are implemented in a safe railway. The results of this paper, the railway sector through the national Intelligent Transportation Systems to develop and introduce strategies to provide operational direction is expected to be present.

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Design of Intelligent Transportation Control System Based on Blockchain Technology

  • Xia, Wei
    • Journal of Information Processing Systems
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    • v.18 no.6
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    • pp.763-769
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    • 2022
  • Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

Intelligent Transportation Systems and Intermodal Transportation Information System for Railroad (교통시스템 정보화와 철도중심의 연계교통정보시스템)

  • 남두희;이진선
    • Journal of the Korean Society for Railway
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    • v.6 no.1
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    • pp.73-79
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    • 2003
  • The Korean high speed railroad is scheduled to open in 2004. For railroad-based integrated transfer system, it is essential to develop the intermodal information system for easy transfer to other travel modes. The understanding of mode choices by KTX passengers is crucial for the intermodal transportation planning. Recent development of Intelligent Transportation Systems(ITS) made it possible for railroad users to access the transportation information in a cabin or waiting areas at the station. Development of intermodal transportation information system will influence the relative demand for traveling by train from competing other transportation modes. The research is focused on a general overview of the ITS with an emphasis on intermodal transportation information system.

Review of Intelligent Transportation Systems Model Deployment Initiative (지자체 지능형교통체계 구축사업의 평가와 발전방안)

  • Nam Doohee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.4 no.2 s.7
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    • pp.33-43
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    • 2005
  • In autumn 2000, the Korea Ministry of Construction and Transportation (MOCT) announced that Daejeon metropolitan city, Jeonju and Jeju were chosen to showcase deployment of Intelligent Transportation Systems(ITS). The program called the Advanced Transportation Systems Model Deployment Initiatives makes a significant step in Intelligent Transportation Infrastructure (In) in Korea. The Initiative is poised to increase the performance and efficiency of the area's roadway and transportation systems to meet growth demand. Three citie's $\$$50 million Model Deployment Initiative project is poised to increase the performance and efficiency of the area's roadway and transportation systems to meet growth demand. The effort particularly focused on the traveler information systems that should raise the level of ITS awareness in Korea. In this paper, project management, funding, private investment, procedures and detailed review of ITS Model Deployment Initiatives are discussed.

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The Intelligent Blockchain for the Protection of Smart Automobile Hacking

  • Kim, Seong-Kyu;Jang, Eun-Sill
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.33-42
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    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

A Review of Intelligent Self-Driving Vehicle Software Research

  • Gwak, Jeonghwan;Jung, Juho;Oh, RyumDuck;Park, Manbok;Rakhimov, Mukhammad Abdu Kayumbek;Ahn, Junho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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    • pp.5299-5320
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    • 2019
  • Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

Neural Network and Cloud Computing for Predicting ECG Waves from PPG Readings

  • Kosasih, David Ishak;Lee, Byung-Gook;Lim, Hyotaek
    • Journal of Multimedia Information System
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    • v.9 no.1
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    • pp.11-20
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    • 2022
  • In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

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.

The Architecture of an Intelligent Digital Twin for a Cyber-Physical Route-Finding System in Smart Cities

  • Habibnezhad, Mahmoud;Shayesteh, Shayan;Liu, Yizhi;Fardhosseini, Mohammad Sadra;Jebelli, Houtan
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.510-519
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    • 2020
  • Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

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