• Title/Summary/Keyword: Intelligent transportation

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A Study of Establishment of Customized ITS Export Model Considering Development Stage by Country (국별 발전단계를 고려한 맞춤형 ITS 수출 모델 수립 연구)

  • Hong, Suk-Kee;Jo, Nam-Min;Lee, Seung-Jun;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.4
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    • pp.36-53
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    • 2017
  • The global intelligent transport systems (ITS) market is experiencing rapid growth, and domestic ITS companies' efforts to extend its business abroad are steadily increasing. However, due to the burden of costs associated with the overseas expansion and the lack of strategy for local market, domestic companies' contracts for global businesses are far short of the technology. Although the government is actively promoting Korean enterprises' participation to overseas business, it has obvious limits due to the lack of its specialized strategy. This study established a customized export model for the countries in which Korean companies want to enter, and developed a strategy to advance into the local market.

Analysis of Commercial Older Drivers Riskiness using Transport Workers Management System (운수종사자시스템을 활용한 사업용 고령운전자의 위험성 분석)

  • Hur, Jung-Chul;Lee, Choul-Ki;Chon, Chun-Taek
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.6
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    • pp.16-28
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    • 2017
  • In this study, we analyzed the result of new inspection, accidents, penalties, and operation records of the elderly driver's driving aptitude test in the city bus using the Transport Workers Management System and the Digital Tachograph Analysis System(eTAS). As a result of the analysis, the results of the driver aptitude test were similar when compared with the traffic company which has many bus drivers and the well - And it was confirmed that the average number of serious injuries and slight injuries in case of accidents was small. Comparing the number of dangerous driving behaviors per 100 km of driving, the elderly driver of the excellent company showed that the number of dangerous driving behaviors is considerably smaller than other elderly and non - elderly drivers, and that the result of correcting the wrong driving habits.

Performance Evaluation of Improved Fast PMIPv6-Based Network Mobility for Intelligent Transportation Systems

  • Ryu, Seonggeun;Choi, Ji-Woong;Park, Kyung-Joon
    • Journal of Communications and Networks
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    • v.15 no.2
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    • pp.142-152
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    • 2013
  • The network mobility basic support (NEMO BS) protocol has been investigated to provide Internet connectivity for a group of nodes, which is suitable for intelligent transportation systems (ITS) applications. NEMO BS often increases the traffic load and handover latency because it is designed on the basis of mobile Internet protocol version 6 (MIPv6). Therefore, schemes combining proxy MIPv6 with NEMO (P-NEMO) have emerged to solve these problems. However, these schemes still suffer from packet loss and long handover latency during handover. Fast P-NEMO (FP-NEMO) has emerged to prevent these problems. Although the FP-NEMO accelerates handover, it can cause a serious tunneling burden between the mobile access gateways (MAGs) during handover. This problem becomes more critical as the traffic between the MAGs increases. Therefore, we propose a scheme for designing an improved FP-NEMO (IFP-NEMO) to eliminate the tunneling burden by registering a new address in advance. When the registration is completed before the layer 2 handover, the packets are forwarded to the new MAG directly and thereby the IFP-NEMO avoids the use of the tunnel between the MAGs during handover. For the evaluation of the performance of the IFP-NEMO compared with the FP-NEMO, we develop an analytical framework for fast handovers on the basis of P-NEMO. Finally, we demonstrate that the IFP-NEMO outperforms the FP-NEMO through numerical results.

A Safety Analysis Based on Evaluation Indicators of Mixed Traffic Flow (혼합 교통류의 적정 평가지표 기반 안전성 분석)

  • Hanbin Lee;Shin Hyoung Park;Minji Kang
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.1
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    • pp.42-60
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    • 2024
  • This study analyzed the characteristics of mixed traffic flows with autonomous vehicles on highway weaving sections and assessed the safety of vehicle-following pairs based on surrogate safety indicators. The intelligent driver model (IDM) was utilized to emulate the driving behavior of autonomous vehicles, and the weaving sections were divided into lengths of 300 and 600 meters for analysis within a micro-traffic simulation (VISSIM). Although significant differences were found in the average speed, density, and headway between the two sections through t-test results, no significant differences were observed when comparing the number of conflicts per indicator and the vehicle-following pair. Four safety indicators were selected for the mixed traffic evaluation based on their ability to represent risk levels similar to those perceived by drivers. The safety analysis, based on the selected four indicators, determined that autonomous vehicles following other autonomous vehicles were the safest pairing. Future research should focus on integrating these indicators into a single comprehensive index for analysis.

A Survey on the Real Time Vehicle Routing Problems (실시간 차량 경로 계획 문제의 연구 동향)

  • Yang, Byoung-Hak
    • Journal of the Korea Safety Management & Science
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    • v.10 no.1
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    • pp.155-166
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    • 2008
  • During last two decades the transportation system has developed into very intelligent system with GIS, GPS and ITS. The practical transportation management system provides real time response module to manage the customer's order. We have surveyed research papers on the real time vehicle routing problem in last two decades to figure out the dynamic vehicle routing problem. The papers are classified by basic routing algorithms and by managing the dynamic events which are the order management, the routing re-optimization, the routing post-optimization and the waiting strategy.

Comparison of Deep-Learning Algorithms for the Detection of Railroad Pedestrians

  • Fang, Ziyu;Kim, Pyeoungkee
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.28-32
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    • 2020
  • Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

Application and Analysis of 2D FRI (Finite Rate of Innovation) Super-resolution Technique in Vision Navigation (영상 항법에서의 2D FRI (Finite Rate of Innovation) Super-resolution 기법 적용 및 분석)

  • Yoo, Kyungwoo;Kong, Seung-Hyun
    • Transactions of the Korean Society of Automotive Engineers
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    • v.23 no.1
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    • pp.1-10
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    • 2015
  • In urban area, since multipath and signal attenuations frequently occur due to street trees, street lights and buildings, it is difficult to obtain accurate navigation solution using GPS. As these problems also impact negatively on the INS/GPS coupled system, implementing advanced transportation systems such as autonomous navigation system and Intelligent Transportation System (ITS) become quite hard. For this reason, to alleviate deterioration of navigation system performance in urban area, direction information extraction algorithm using vision system is proposed in this paper. 2D Finite Rate of Innovation (FRI) technique is applied to extract lane edges. The proposed technique is simulated using road images and feasibility of proposed technique is analyzed through the simulation results.

An Efficient Anonymous Authentication Scheme with Secure Communication in Intelligent Vehicular Ad-hoc Networks

  • Zhang, Xiaojun;Mu, Liming;Zhao, Jie;Xu, Chunxiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3280-3298
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    • 2019
  • Vehicular ad-hoc networks (VANETs) have become increasingly significant in intelligent transportation systems, they play a great role in improving traffic safety and efficiency. In the deployment of intelligent VANETs, intelligent vehicles can efficiently exchange important or urgent traffic information and make driving decisions. Meanwhile, secure data communication and vehicle's identity privacy have been highlighted. To cope with these security issues, in this paper, we construct an efficient anonymous authentication scheme with secure communication in intelligent VANETs. Combing the ElGamal encryption technique with a modified Schnorr signature technique, the proposed scheme provides secure anonymous authentication process for encrypted message in the vehicle-to-infrastructure communication model, and achieves identity privacy, forward security, and reply attack resistance simultaneously. Moreover, except the trusted authority (TA), any outside entity cannot trace the real identity of an intelligent vehicle. The proposed scheme is designed on an identity-based system, which can remove the costs of establishing public key infrastructure (PKI) and certificates management. Compared with existing authentication schemes, the proposed scheme is much more practical in intelligent VANETs.

Effective Design of Inference Rule for Shape Classification

  • Kim, Yoon-Ho;Lee, Sang-Sock;Lee, Joo-Shin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.417-422
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    • 1998
  • This paper presents a method of object classification from dynamic image based on fuzzy inference algorithm which is suitable for low speed such as, conveyor, uninhabited transportation. At first, by using feature parameters of moving object, fuzzy if - then rule that can be able to adapt the wide variety of surroundings is developed. Secondly, implication function for fuzzy inference are compared with respect the proposed algorithm. Simulation results are presented to testify the performance and applicability of the proposed system.

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