• Journal of the Korean Society of Safety
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• v.26 no.3
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• pp.91-97
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• 2011

The weight of elderly people in Korea has been increasing. Statistics show that the percentage of the elderly people in Korea was 3.1% in 1970; 3.8% in 1980; 5.1% in 1990, and 7.2% in 2000. Based on this trend, thus, the number of elderly people could be estimated to be 14% of the whole Korean population in 2018. This reveals that Korea is entering a super-aging society with remarkable fast pace. In such a change, the statistics related to elderly people driving license and the occurrence of traffic accidents are showing a noticeable numerical value. The number of traffic accident fatality in Korea ranks the highest value in OECD Countries. However, the research on old drivers in the nation is going on partially centering on system improvement and management scheme. Thus, first of all, researches about the linkage & characteristics between the driving behavior of old drivers and traffic accident should be implemented, in order properly to draw system improvement and management scheme for the old drivers. Therefore, the focus of this study is the influence model for discerning the severity of the age-old-caused traffic accidents by inquiring into the relation between the Driving Aptitude Test items that make it possible to measure their behavioral characteristics and influential factors by age group on the basis of the data on traffic accidents. The analysis results can be used as basic data for suggesting the behavioral research and countermeasure for traffic safety and its management for old driver in preparation for the aging society.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.3
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• pp.16-25
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• 2013

Now it's a trend to install a series of white fluorescent light and orange high pressure sodium lamps because tunnel lighting should be opaque to the safety of drivers from soot, dust, humidity, and fog. Also fluorescent lighting is replaced to LED due to the fact that it improves amenity and object recognition and LED lighting has gradually been improved its nature. In this paper, we have implemented the circuits of the yellow series of high-pressure sodium lamps and white series of LED lights at one board to improve the transparency and recognition of objects. It is possible for inductive high-pressure sodium lamps and the capacitive LED drivers to circuit without power factor compensation. Two circuit parts share only a small number of parts, so low cost LED drivers compared to conventional ones are possible. Therefore, the implementation of the hybrid lighting with high-pressure sodium lamps and LED lights that can be driven at the same time by one driving circuit is possible. The LED capacitive power factor was 0.91 while individually implemented the sodium lamp power factor was 0.98. It shows not only the 2% improvement of hybrid forms but also the efficiency and THD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1247-1254
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• 2009

The purpose of the present study was to compare and analyze the differential effects of in-vehicle electronic device usage types(searching for targeted destinations in navigational purpose, watching TV in entertain purpose, and dialing a cellular-phone in phone-usage purpose) on driver's front-to-rear-end collision avoidance behavior, and to find effective collision warning format for this behavior. The result indicated that (1) the drivers showed more impaired collision avoidance performances when they were asked to search the name of targeted destination than the other task requirements, and (2) auditory warning appeared to be most effective among the other types of warning. In particular, it was suggested that the "Visual-Only" collision warning could induce most undesirable result when the drivers were engaged in both visual and auditory information processing.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.97-106
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• 2003

When a route choice is done under uncertainty, a driver has some expectation of traffic conditions that will occur according to the route chosen. This study tries to build a framework in which we can observe the learning behavior of the drivers' expectations of the travel time under nonstationary environment. In order to investigate how drivers have their subjective expectations on traffic conditions in response to public information, a numerical experiment is carried out. We found that rational expectations(RE) formation about the route travel time can be expressed by the adaptive expectation model when the travel time changes in accordance with the nonstationary process which consists of permanent shock and transient shock. Also, we found that the adaptive parameter of the model converges to the fixed value corresponding to the route conditions.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.63-74
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• 2009

One of the effective countermeasures for preventing traffic accidents is to provide traffic safety warning information to drivers. Provision of warning information would lead to safer driving to avoid accident occurrence. This study investigated the effects of in-vehicle warning information on driver's behavior. A variety of warning information contents using text, sound, and pictograms were prepared for the field experiments. Individual vehicle speed and acceleration data, which represent quantitative drivers' behavior in response to in-vehicle warning information, were collected using differential global positioning systems (DGPS). Statistical analyses including ANOVA and Tukey's pairwise comparison were conducted. It is expected that the results could be invaluable for designing more effective warning information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.46-56
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• 2015

The purpose of this study is to find out the effectiveness of drivers' satisfaction over protected and permissive left-turn (PPLT) traffic signal operation. A structural equation model was established for analyzing the effectiveness of various drivers' factors (e.g., personal characteristics, driving attitude, expectation to PPLT, etc.) on the PPLT preference based on questionnaire survey. As a result, the analysis is satisfied with the critical values, such as Q value, RMR, GIF, AGIF, and NFI. The study reveals that PPLT preference increases in case of driver who is male with long social carrier related to transportation affaire and long driving experience without traffic accident involvement. Moreover, PPLT preference increases as the expectation of PPLT to improvement of traffic safety, traffic operation, and traffic environment increases. Therefore, it is recommended that the PPLT should be preferentially operated in urban area of less traffic accidents and the promotion of PPLT be actively conducted for positive effectiveness.

• Safety and Health at Work
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• v.10 no.1
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• pp.95-102
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• 2019

Background: In a cluster-randomized trial, the Safety and Health Involvement For Truck drivers intervention produced statistically significant and medically meaningful weight loss at 6 months (-3.31 kg between-group difference). The current manuscript evaluates the relative impact of intervention components on study outcomes among participants in the intervention condition who reported for a post-intervention health assessment (n = 134) to encourage the adoption of effective tactics and inform future replications, tailoring, and enhancements. Methods: The Safety and Health Involvement For Truck drivers intervention was implemented in a Web-based computer and smartphone-accessible format and included a group weight loss competition and body weight and behavioral self-monitoring with feedback, computer-based training, and motivational interviewing. Indices were calculated to reflect engagement patterns for these components, and generalized linear models quantified predictive relationships between participation in intervention components and outcomes. Results: Participants who completed the full program-defined dose of the intervention had significantly greater weight loss than those who did not. Behavioral self-monitoring, computer-based training, and health coaching were significant predictors of dietary changes, whereas behavioral and body weight self-monitoring was the only significant predictor of changes in physical activity. Behavioral and body weight self-monitoring was the strongest predictor of weight loss. Conclusion: Web-based self-monitoring of body weight and health behaviors was a particularly impactful tactic in our mobile health intervention. Findings advance the science of behavior change in mobile health intervention delivery and inform the development of health programs for dispersed populations.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.25-31
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• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.70-82
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• 2022

At the current stage of a semi-autonomous vehicle, there are situations in which the vehicle has to request take-over control to the driver quickly. However, current self-driving cars use only simple messages and warning sounds to notify drivers when handing over control, so they do not adequately convey considerations of individual characteristics or explanations of various emergent situations. This study investigated how visual and auditory information and the efficacy of drivers in self-driving cars can improve efficient take-over requests between the car and the driver. We found that there were significant differences in driver's cognitive load, reliability, safety, usability, and usefulness according to the combination of three visual and auditory information provided in the experiment of the take-over request situation. The results of this study are expected to help design self-driving vehicles that can communicate more safely and efficiently with drivers in urgent control transition situations.