• Title/Summary/Keyword: u-Transportation

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Traffic Flow Management under Ubiquitous Transportation System Environments (유비쿼터스 교통 환경하에서 교통류 관리구상)

  • Park, Eun-Mi
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.179-186
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    • 2008
  • It is crucial in traffic flow management to maintain productivity and the traffic stability at the same time especially under congested traffic conditions. This issue has not been explicitly addressed under the intelligent transportation system environments. However, the ubiquitous transportation system environments make it possible to collect the data for each vehicle's position and velocity and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communications. In this paper, a preventive traffic flow management scheme is proposed, in which the objective is to maintain traffic flow stability while the productivity of the system is not decreased. The management scheme is proposed based on Greenshield's model because it is simple and easy to handle. It is considered that further research should be performed to evaluate the various traffic flow models.

An Integration of Searching Area Extraction Scheme and Bi-directional Link Searching Algorithm for the Urban ATIS Application (도시부 ATIS 효율적 적용을 위한 탐색영역기법 및 양방향 링크탐색 알고리즘의 구현)

  • 이승환;최기주;김원길
    • Journal of Korean Society of Transportation
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    • v.14 no.3
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    • pp.45-59
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    • 1996
  • The shortest path algorithm for route guidance is implicitly required not only to support geometrical variations of transportation network such as U-TURN or P-TURN but to efficiency search reasonable routes in searching mechanism. The purpose of this paper is to integrate such two requirements ; that is, to allow U-TURN and P-TURN possibilities and to cut down searching time in locating routes between two points (origin and destination) in networks. We also propose a new type of link searching algorithm which can solve the limitation of vine building algorithm at consecutively left-turn prohibited intersections. The test site is a block of Gangnam road network that has some left-turn prohibited and allowed U-TURN intersections. Four models have been identified to be comparatively analyzed in terms of searching efficiency. The Models are as follows : (i) Model 1 - Link Searching Dijkstra Algorithm without Searching Area Extraction (SAE) ; (ii) Model 2 - Link Searching Dijkstra Algorithm with SAE ; (iii) Model 3 - Link Searching Bidirectional Dijkstra Algorithm without SAE ; and (iv) Model 4 - Link Searching Bidirectional Dijkstra Algorithm with SAE. The results of comparative evaluation show that Model 4 can effectively find optimum path faster than any other models as expected. Some discussions and future research agenda have been presented in the light of dynamic route guidance application of the urban ATIS.

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Cross-cultural Differences in Driver's Traffic attitude -Comparison of Korea, U.S.A. Canada and Japan- (운전자의 교통태도에 대한 비교 연구 -한국, 미국, 카나다, 일본-)

  • 이순철
    • Journal of Korean Society of Transportation
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    • v.9 no.1
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    • pp.19-28
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    • 1991
  • This study aims to seize the differences in drivers' attitudes and to speculate about the attitudes which may be causally related to traffic accidents based on data collected from group survey questionnaire in the four countries. The questionnaire was composed of 9 problem areas and prepared in Japanese English and Korean languages. The survey was conducted in Japan Canada U.S.A and Korea in 1987 The present study analysed the driver's attitudes toward behaviour of pedestrians traffic signal and causes of traffic accidents. The main results are :(1) The order of high percentage of those who cited the pedestrians as major cause of accidents was Korea Japan, Canada and U,S,A This markes the very high number of accidents involving pedestrians in Korea. (2) The percentage of who answered that most drivers started before the sign changed to Go sign at an intersection were higher in Japan and Korea than in U.S.A (3) Regarding the caues of accidents if the drivers were to meet with an accident the percentage of responses attributing faults to themselves for the accident was very high in Japan. Korea came next. In contrast the percentage of responses attributing faults to others is higher in Canada and U.S.A than Japan and Korea.

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Study on Calculation of Bus Stop Set-back Distance to Operate Turn lanes at Intersection on Median Exclusive Bus Lanes (중앙버스전용차로 교차로에서 회전차로 운영시 버스정지선 후퇴거리 산정에 관한 연구)

  • Im, Dong-wook;Lee, Young-Ihn
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.6
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    • pp.80-89
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    • 2016
  • The median exclusive bus lanes with the purpose of improving public transport as part of a public transport promoting policy propel to improves the speed of the bus and guarantee punctuality security of public transportation for citizen satisfaction. In Median Exclusive bus lanes, Intersection operational methods are classified as turn prohibition, left turn, left turn U-Turn after turn prohibition. However, there are not clear criteria for applying for turn left U-Turn and related researches. The purpose of this study is to search a method for more safely operation when we operate turn left U-Turn in median exclusive bus lanes intersection. As a result, Bus stop in median exclusive bus lane should set back 12m for left turn, 17m for left turn U-turn during 60km/h and set back 13m for left turn, 17m for left turn U-turn during 50km/h.

Contactless User Identification System using Multi-channel Palm Images Facilitated by Triple Attention U-Net and CNN Classifier Ensemble Models

  • Kim, Inki;Kim, Beomjun;Woo, Sunghee;Gwak, Jeonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.33-43
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    • 2022
  • In this paper, we propose an ensemble model facilitated by multi-channel palm images with attention U-Net models and pretrained convolutional neural networks (CNNs) for establishing a contactless palm-based user identification system using conventional inexpensive camera sensors. Attention U-Net models are used to extract the areas of interest including hands (i.e., with fingers), palms (i.e., without fingers) and palm lines, which are combined to generate three channels being ped into the ensemble classifier. Then, the proposed palm information-based user identification system predicts the class using the classifier ensemble with three outperforming pre-trained CNN models. The proposed model demonstrates that the proposed model could achieve the classification accuracy, precision, recall, F1-score of 98.60%, 98.61%, 98.61%, 98.61% respectively, which indicate that the proposed model is effective even though we are using very cheap and inexpensive image sensors. We believe that in this COVID-19 pandemic circumstances, the proposed palm-based contactless user identification system can be an alternative, with high safety and reliability, compared with currently overwhelming contact-based systems.