• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.969-972
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• 2013

In this paper, we presented high-pass OBU device to support eco driving for commercial vehicles such as heavy trucks. The proposed OBU is convergence OBU (On Board Units) platform with high-pass toll functions and eco driving functions. In order to verity performance of proposed OBU device, we conducted test drives on road.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• Korean Journal of Human Ecology
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• v.24 no.3
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• pp.341-358
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• 2015

This study aims to identify predictors of driving cessation among Korean elderly. Data from 2011 Elderly Survey conducted by Ministry of Health and Welfare and Korea Institute for Health and Social Affairs were used for the analysis. Based on Webber, Porter, Menec(2010)'s comprehensive theoretical framework for mobility, the model of this study tests five major determinants of driving cessation including financial, psychosocial, environmental, physical and cognitive factors. Results of logistic regression analysis showed that economic status, marital status, contacts with relatives and friends, residential location, taking medication, muscle strength, age, gender, and job were significant predictors of driving cessation of older drivers. Specifically, lower economic status, unmarried status, less contacts with relatives and friends, living in the city, taking medication, weaker muscle strength, older age, female, non-working status were significant risk factors for driving cessation. Practical implications in light of study findings were discussed.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.449-451
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• 2002

We reported the algorithm of driving scheme that enhances moving picture property by improving gray-to-gray response time. Here, we report result of simulation for estimation of driving voltage to reduce response time, and experimental result. We investigated optimization of algorithm so that minimum size of LUT can support to reducing the gray-to-gray response time within 1 frame period, and with single algorithm it is possible to apply the algorithm to various kinds of LC material. So in our system there is no external EEPROM.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.1
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• pp.48-55
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• 2009

In order to keep safe driving conditions under road networks, there are several formations such as road structure, road surface condition, traffic occupancy and supplement of an accurate information of traffic status ahead To support safe-driving on each road formation, each formation is supplied with various information to help the driver. However, in some cases like rapid status change at local-scale geography, traffic information systems often displays insufficient information because of the lack of information correlation. In order to accurately aware the driver, all road formation must be in sync. It is important to supply accurate information to the driver because this information directly impacts the drivers on the road. This paper discusses the amber information to keep the least safety driving over road formations including tunnels and bridges. This paper also will propose the informations for safe-driving conditions, information linkage on the road and rule-base safety information, as ITS technology, being displayed for all drivers under the worst weather conditions.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.619-624
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• 2010

The traffic accidents of the aged are increasing because old people generally experience a decline of physical functions and judgment but their dependence on automobiles increases. In order to investigate the older drivers' response to traffic signs and surrounding environment according to changing driving brightness, this study measured the visual cognitive behavior, driving behavior, and subjective evaluation while the driving brightness was changed using a driving simulator. Furthermore, the drivers who recognized traffic signs and those who did not were compared. As a result, it was found that some older drivers had declined ability of cognition, some failed to adapt to rapid brightness change even if sufficient attention was given to traffic sign, and some could not safely control the vehicle when approaching intersections. Therefore, the development of support systems for aged drivers in traffic environment is necessary in the future.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.283-289
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• 2011

The purpose of this study is to provide some basic materials for the driving rehabilitation, by analyzing the presence and needs of the driving rehabilitation, which is recognized by the Occupational therapist. This study analyzed 83 survey questionnaires given to occupational therapist in Busan and Kyoung-nam. Most Occupational therapists does not receive lecture and education of driving rehabilitation, 62 Occupational therapist does not driving rehabilitation intervention. Most Occupational therapist mentioned driving rehabilitation needs. Driving rehabilitation influence on rehabilitation of clients and support activities of daily life.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.116-129
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• 2023

Recently, interest in autonomous driving has drawn attention to autonomous cooperative driving, which considers the development of driving technology of autonomous vehicles and the development of infrastructure that constitutes a driving environment. According to the concept of autonomous cooperative driving, This study analyzes the new infrastructure for autonomous driving that can complement the information of existing precise road maps and adding HD map layer as the new infrastructure. The new infrastructure for autonomous driving presented two types of improved facilities and one type of sensor only facility. Analysis of HD maps shows that information such as junction points rarely changes, but it is expected that infrastructure for autonomous driving can be added to convey the meaning of paying attention to obstacles that may arise at the junction. In this way, the new infrastructure for autonomous driving needs to support the roles of guidance, instruction, and attention that existing road facilities.