• Journal of the Ergonomics Society of Korea
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• v.32 no.2
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• pp.167-177
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• 2013

Objective: This study aims to compare the usefulness of subjective measures which are comprised of existing methods like NASA-TLX, Bedford-scale and ZEIS and newly developed method like DALI in measuring drivers' mental workload in terms of validity, sensitivity and diagnosticity. Background: Nowadays, with the development of intelligent vehicle and HMI, mental workload of driver has become more and more important. For this reason, the studies on drivers' mental workload about driving situation and the use of information technology equipment such as mobile phones and navigations were conducted intensively. However, the studies on measuring drivers' mental workload were rarely conducted. Moreover, most of studies on comparison of subjective measures were used with performance based measure. However, performance based measures can cause distraction effect with subjective measures. Method: Participants (N=19) were engaged in a driving simulation experiment in 2 driving contexts (downtown driving and highway driving context). The experiment has 2 sessions according to driving contexts. The level of difficulties by driving contexts were adjusted according to existence of intersections, traffic signs and signals, billboards and the number of doublings. Moreover, as criteria of concurrent validity and sensitivity, the EEG data were recorded before and during the sessions. Results: The results indicated that all subjective methods were correlates with EEG in high-way driving. On the contrary to this, in downtown driving, all subjective methods were not correlates with EEG. In terms of sensitivity, multi-dimensional scales (NASA-TLX, DALI) were the only ones to identify differences between high way and downtown driving. Finally, in terms of diagnosticity, DALI was the most suitable method for evaluating drivers' mental workload in driving context. Conclusion: The DALI as newly developed method dedicated to evaluate driver's mental workload was superior in terms of sensitivity and diagnosticity. However, researchers should consider the characteristics of each subjective method synthetically according to research objective by selecting the method in subjective measures. Application: The results of this study could be applied to the intelligent vehicle and next generation of HMI design to decrease mental workload of driver and for the development of new subjective method in vehicle domain.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.145-154
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• 1998

The effects of secondary task on driving performance and subjective workload were investigated during a simulated driving. The driving performance was determined by the appropriateness of break timing. The driving simulator was provided by the Korea Road Traffic Safety Association. The subjective workload was tested by using a multidimensional measure such as NASA-TLX. Road was categorized into two types: narrow alley and wide street. The secondary task included pushing the number on the cellular phone, pushing radio channel, and conversing with a passenger. Seventeen subjects volunteered in the study. The data were analyzed by using SAS. Results showed that using the cellular phone and pushing channel during driving caused 3∼22% decline of driving performance and 42∼59% increase of subjective workload respectively. These results indicated that the secondary task could be potentially dangerous although there was not a significant performance decrease due to the notable increase of mental workload. In the future, if we can use a more sensitive and realistic driving simulator, the effects of secondary task under a dynamic driving situation can be investigated.

• Journal of the Korean Society of Safety
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• v.28 no.5
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• pp.66-70
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• 2013

This study examined the relative effects of education and eco-IVIS(in-vehicle information system) to reduce fuel consumption and greenhouse gas emissions. Also the study investigated the increasing of driving workload when drivers interact with intervention technique. Thirty participants randomly assigned into two groups(training and eco-IVIS) and conducted driving before and after the each intervention technique. While driving, we observed three driving behaviors: Frequency of excessive RPM, percent of speeding, and mean fuel efficiency. Also the Driver Activity Load Index was used to rate participants' subjective ratings of driving workload. Although the results showed positive impact of both education and eco-IVIS to increasing the eco-driving behaviors, eco-IVIS was more effective than education. However, we found comparable level of driving workload in the education and eco-IVIS.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.37-45
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• 2011

The main objective of this study is two-fold: 1) to analyze the effect of PG technology application on road user's satisfaction and driving speed, and 2) to investigate the relationship between driver's subjective workload level and their reactions related to the PG technology application. Based on the result of field observation, the experimental scenario for driving simulation study was prepared. The experimental results showed that drivers were more satisfied to the road condition with PG technology applied, and even the pattern of speed reduction was more stable than control condition. The pattern of speed reduction along driver's subjective driving workload level were slightly different by physical road condition, and road user's satisfaction was revealed to be negatively correlated with their subjective driving workload level. This result indicates that depending on situation and driver characteristic, information for the drivers could be nothing more than nuisance that just distracts drivers. In order to facilitate the implementation of PG technology in Korea, further study on related human factors, especially for those who are weak in traffic situations, is recommended.

• ETRI Journal
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• v.37 no.3
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• pp.626-636
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• 2015

This paper proposes an adaptive multimodal in-vehicle information system for safe driving. The proposed system filters input information based on both the priority assigned to the information and the given driving situation, to effectively manage input information and intelligently provide information to the driver. It then interacts with the driver using an adaptive multimodal interface by considering both the driving workload and the driver's cognitive reaction to the information it provides. It is shown experimentally that the proposed system can promote driver safety and enhance a driver's understanding of the information it provides by filtering the input information. In addition, the system can reduce a driver's workload by selecting an appropriate modality and corresponding level with which to communicate. An analysis of subjective questionnaires regarding the proposed system reveals that more than 85% of the respondents are satisfied with it. The proposed system is expected to provide prioritized information through an easily understood modality.

• Journal of the Ergonomics Society of Korea
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• v.18 no.2
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• pp.103-120
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• 1999

The purpose of this study was to evaluate the manual workload in repetitive wrist and finger motion. To evaluate manual workload, angular displacement of the joint, EMG of the muscle and subjective rating were studied. Both wrist motion and finger motion were studied. A screw-driving task was used for the wrist motion experiment. A keyboard typing task was used for the finger motion experiment. All finger joint angles and wrist angles were measured by an angle-measuring glove($CyberGlove^{TM}$, Virtual Technologies, Inc.). Surface EMG was recorded from FCU muscle and FDS muscle simultaneously with the angle measurement. Subjective ratings of exertion were also recorded using the modified Borg's CR-10 scale. Repetition rates of 0.5, 1, 2 motions per second were used with each task. As a result, manual workload increased with increasing repetitiveness. Peak spectral magnitude and frequency components corresponded closely with joint angular displacement amplitudes and repetition rates. Results of the correlation analysis showed that there were significant correlation among EMG, frequency-weighted motion and subjective measurement. Both EMG and frequency-weighted filtering showed consistent workload estimation with increasing task frequency. Subjective ratings showed slight over-estimation of the workload as the task frequency is increased.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.109-118
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• 2009

While driving, the manual use of a mobile phone is heavily restricted due to the interference with the primary driving task. An alternative would be the use of speech interface. The current study aims to provide a guideline to implementation of a speech interface to the mobile phone. To do so, an expert evaluation was made and it revealed that a speech interface requires less workload, less performance degradation of the driving task than that of the keypad interface. To make speech interfaces more usable, new improvements are suggested. Subjective workload can be reduced and user satisfaction can be improved without degrading the primary task performance, for instance, by letting the user interrupt the speech of the phone, eliminating the repetitive words, letting the user know clearly what makes an error, providing a way to go back to the previous state, reducing the usage of keypad buttons and reducing the amount of the information on the screen.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.26-33
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• 2009

The directions of the road are divided into two, the right-hand side and left-hand side of the road, by the convention and specific native method in the world. This paper deals with the characteristics and behaviors of drivers who are accustomed to driving on right-hand side of the road, drive with a handle on the left-hand side, and comparing with left-hand side drivers. The driver's eye movements were measured by eye camera and questionnaires were used for measuring subjective evaluation such as driving mental workload. The experimental results indicated even if the experts who had much experience on right-hand side driving, they had lower driving skill than novice driver, accustomed to driving on left-hand side. In terms of mental workload, MCH rating scale and MNASA-TLX, the right-hand side drivers were in lower stress condition than the left-hand side drivers because of having much driving experience. However, they conducted a few mistakes by confusing the position of turn signal and windshield wiper because of their driving habit or traits and it lead to operation mistakes. These results can be applied effectively to develop the driving support information with changed environments.

• IE interfaces
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• v.10 no.1
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• pp.145-154
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• 1997

In developing the HMI(Human-Machine Interface) evaluation system for the IVNS(In-Vehicle Navigation System), design guidelines and evaluation methods are the most crucial problems for its use and efficiency. As the part of this system, focused on the final product of the database, subjective mental workload assessment is seriously considered to evaluate the driver's own driving task using the IVNS. This paper suggests the methodology for the ergonomic assessment of the IVNS that corresponds to the subjective measurement of the driver's mental workload by rating his or her own driving task. For this approach, Revision of NASA-Task Load Index(RNASA-TLX) was developed which translated and revised the version of NASA-TLX that is generally accepted an efficient and powerful method for evaluating the in-vehicle information systems. To verify the RNASA-TLX, an experiment was conducted in a real road situation, because the result of the laboratory approach is uncertain and has the differences from the real road test.

• ETRI Journal
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• v.45 no.1
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• pp.75-92
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• 2023

Level 3 autonomous vehicles require conditional autonomous driving in which autonomous and manual driving are alternately performed; whether the driver can resume manual driving within a limited time should be examined. This study investigates whether the demographics and subjective driving tendencies of drivers affect the take-over performance. We measured and analyzed the reengagement and stabilization time after a take-over request from the autonomous driving system to manual driving using a vehicle simulator that supports the driver's take-over mechanism. We discovered that the driver's reengagement and stabilization time correlated with the speeding and wild driving tendency as well as driving workload questionnaires. To verify the efficiency of subjective questionnaire information, we tested whether the driver with slow or fast reengagement and stabilization time can be detected based on machine learning techniques and obtained results. We expect to apply these results to training programs for autonomous vehicles' users and personalized human-vehicle interfaces for future autonomous vehicles.