• Journal of the Ergonomics Society of Korea
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• v.36 no.2
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• pp.87-108
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• 2017

Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.52-69
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• 2020

Considering the need for an infrastructure-level review, this study analyzed the impact of truck platooning on freeway traffic flow and the effect of dedicated lanes based on domestic road and traffic conditions. According to the study, the higher traffic volume and truck ratio, the higher ratio of platoons and the greater size of platoons are formed, which results in greater effect of increasing the average speed of the network. Therefore, the routes with heavy traffic and heavy cargo traffic could be positively considered for truck platooning. However, the analysis showed that the effect of increasing the average speed of the entire network is difficult to expect in the event of a queue due to entry and exit, and that the overall network's throughput could be reduced. Therefore, traffic operation strategies associated with the access road, such as securing capacity of the connection, are needed to maximize the effect of truck platooning. When it comes to the effect of dedicated lane, it could have a positive effect only if one lane was fully operated by automated trucks under the condition of 100% MPR, which allowed positive effects in all aspects, such as higher average speed, throughput, and reduced conflict rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• YAKHAK HOEJI
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• v.52 no.2
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• pp.137-146
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• 2008

Even though driving under the influence of drug (DUID) is a worldwide problem, we, Korea has no regulation system yet except for alcohol, and there are little cases reported related to DUID. In order to investigate the type of abused drugs for drivers in Korea, we tried to analyze controlled and non-controlled drugs in alcohol-positive blood samples. 275 whole bloods, which were positive for alcohol on the roadside test, were collected from the police for two months ($Nov.{\sim}Dec.$ 2006). The analytical strategy was constituted of three steps: First, alcohol in blood samples were confirmed and quantified by gas chromatography. Second, controlled drugs were screened by $Evidence_{investigator}\;^{TM}$ (Randox, U.K.) as preliminary test. It was based on immunoassay by biochip array analyzer. Nine groups of drug abuse were screened: amphetamines, methamphetamines, cannabis, cocaine, opiates, barbiturates, methadone, benzodiazepines I (oxazepam) & II (lorazepam). Finally, confirmation of these drugs was performed by GC-MS. Blood samples were extracted by solid-phase extraction by $RapidTrace^{TM}$ (Zymark, U.S.A.). After trimethylsilyl (TMS) derivatization, eluates were analyzed to GC-MS. Total 49 drugs were investigated in this study including controlled drugs, antidepressants, 1st generation antihistamines, dextromethorphan, nalbuphine, ketamine, etc. For rapid detection, we developed the automated identification system. It was made up a new software, "DrugMan", modified Chemstation data analysis menu and newly developed macro modules. A series of peak selection, identification and reporting of the results were performed automatically by this system. Concentrations of alcohol in 275 blood samples were ranged from 0.011 to 0.249% (average, 0.119%). Among 149 blood samples, just six samples (4.0%) were showed positive results to the immunoassay: one methamphetamine and five benzodiazepines group I. By GC-MS confirmation, only benzodiazepines were detected and methamphetamine was not detected from immunoassay positive blood sample. Besides these drugs, 5 chlorpheniramines, dextromethorphan, diazepam, doxylamine, ibuprofen, lidocaine and topiramate were also detected in whole bloods by GC-MS. Conclusively, the frequency of drug abuse for Korean drivers was relatively low. There was none case which illegal drug was detected. However these results were limited to alcohol positive blood samples, so it is necessary to analyze more samples including alcohol negative blood.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.15-29
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• 2021

The signal intersection is the most challenging space for autonomous vehicles. To promote the safe driving of autonomous vehicles on urban roads with traffic signals, autonomous vehicles need to receive traffic signal information from infrastructure through V2I communication. Thus, a protocol for providing traffic signal information was added to the standard traffic signal controller specification of the National Police Agency. On the other hand, there are technical limitations when applying this to digital traffic signal controllers because the protocols are defined mainly for analog traffic signal controllers. Therefore, this study proposes developing a signal information linkage module to provide traffic signal information from a digital traffic signal controller to an autonomous vehicle and an algorithm improvement method that can provide accurate traffic signal information at the time of traffic signal transition.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.499-523
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• 2017

Objective: This study is to provide a foundation for developing comprehensive ergonomic design guidelines for in-vehicle information systems (IVIS) by giving an overview of existing researches as well as setting further research directions. Background: The drivers get much more information recently while interacting with new safety functions of the cars. To avoid cognitive overload of the drivers, IVIS should be deigned appropriately by considering various human factors and task conditions. Method: We gathered, analyzed, and summarized ergonomic researches concerned with IVIS design conducted inside and outside Korea according to a categorization system proposed in the study. Frequency analysis was conducted for figuring out what kind of issues took major part of the researches, and their trends across time and regions. Results: Compared to domestic researches, those done in overseas tend to deal with more variety of independent, dependent and extraneous variables. The overseas researches also showed a tendency to get ahead in making ergonomic guidelines for IVIS design by adapting and integrating the results from previous researches. Conclusion and Application: There have been many researches regarding with ergonomic IVIS design, but some of their results became old-fashioned as the technology evolved. Not many researches have considered diverse human factors regarding the drivers' characteristics except age and gender. It is expected that researchers and designers take advantage of this study to find and review relevant results and set out issues of their own for more progressive researches of the field.

• Atmosphere
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• v.17 no.4
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• pp.339-348
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• 2007

Global Environment Laboratory at Yonsei University in Seoul ($37.57^{\circ}N$, $126.95^{\circ}E$) has carried out the ozone layer monitoring program in the framework of the Global Ozone Observing System of the World Meteorlogical Organization (WMO/GAW/GO3OS Station No. 252) since May of 1984. The daily measurements of total ozone and the vertical distribution of ozone amount have been made with the Dobson Spectrophotometer (No.124) on the roof of the Science Building on Yonsei campus. From 2004 through 2006, major parts of the manual operations are automated in measuring total ozone amount and vertical ozone profile through Umkehr method, and calibrating instrument by standard lamp tests with new hardware and software including step motor, rotary encoder, controller, and visual display. This system takes full advantage of Windows interface and information technology to realize adaptability to the latest Windows PC and flexible data processing system. This automatic system also utilizes card slot of desktop personal computer to control various types of boards in the driving unit for operating Dobson spectrophotometer and testing devices. Thus, by automating most of the manual work both in instrument operation and in data processing, subjective human errors and individual differences are eliminated. It is therefore found that the ozone data quality has been distinctly upgraded after automation of the Dobson instrument.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.188-199
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• 2018

In this study a novel dynamic lane-level location referencing method(LLRM) was developed. The terminologies were defined and the prerequisites were suggested for the LLRM. Then, the logical and physical data formats were proposed, followed by the development of encoding and decoding algorithms. To conduct a performance test of the proposed method, two different high precision digital maps were prepared as well as an evaluation tool. The test results demonstrated that the proposed method works perfectly in terms of accuracy. The processing speed and the data size were found to be less efficient, but it is expected that the defect would be compensated soon enough due to the fast growing technology of ICT and computer hardwares.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.163-174
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• 2002

Speeding has been reported as one of the major causes for fatal traffic accidents in Korea. The resolution against this dangerous speeding comes to make the automated speed enforcement system an enforcement tool. The speed detection device, which measures speeds of each incoming vehicles using double loop sensors, requires high accuracy. The object of this study is to develop an accurate speed measurement algorithm using double loop detectors. Some important findings are summarized as follows: 1) It was found that speed measurement errors are caused by scanning rate, distance of two loops, irregular vehicle trajectories, multiple vehicles in detection zone. 2) A proposed algorithm using two signal set proved to reduce variance as well as mean of speed measurement. 3) A proposed filtering algorithm was effective to filter irregular driving vehicles and multiple vehicles in detection zone. A comprehensive field test of developed algorithm resulted in significant improvement of speed measurement accuracy.