• Title/Summary/Keyword: Driving score

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Effectiveness of golf skills to average score using records of PGA, LPGA, KPGA, KLPGA : Multi-group path analysis (프로골프 경기기록을 활용한 다중집단분석 : 경로분석 적용)

  • Kim, Sae Hyung;Cho, Jung Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.3
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    • pp.543-555
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    • 2013
  • This study is to analyze effectiveness of golf skills (driving distance, rating of fairway, green in regulation, sand save ratio, recovery ratio, putting average) to average score using records of PGA, LPGA, KPGA, KLPGA. Independent variables were driving distance, rating of fairway, green in regulation, sand save ratio or recovery ratio, putting average. Dependent variable was the scoring average in this study. To analyze these variables, multi-group (PGA vs LPGA, KPGA vs KLPGA, PGA vs KPGA, LPGA vs KLPGA) path analysis was used through AMOS 18.0 program and significance level was set at 0.05. As the result, the variables that show significant differences of path coefficient between PGA model and LPGA model were driving distance and green in regulation to average score. The variables that show significant differences of path coefficient between KPGA model and KLPGA model were driving distance, recovery ratio, and putting average to average score. The variables that show significant differences of path coefficient between PGA model and KPGA model were driving distance, recovery ratio, and putting average to average score. There was not significant difference of path coefficient between LPGA model and KLPGA model.

Quantification Method of Driver's Dangerous Driving Behavior Considering Continuous Driving Time (연속주행시간을 고려한 운전자 위험운전행동의 정량화 방법)

  • Lee, Hyun-Mi;Lee, Won-Woo;Jang, Jeong-Ah
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.4
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    • pp.723-728
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    • 2022
  • This study is a method for evaluating and quantifying driver's dangerous driving behavior. The quantification method calculates various driving information in real time after starting the vehicle operation such as the time that the vehicle has been continuously driven without a break, overspeed, rapid acceleration, and overspeed driving time. These quantified risk of driving behavior values can be individually provided as a safe driving index, or can be used to objectify the evaluation of a group of drivers on roads, or vehicle groups such as cargo/bus/passenger vehicles.

The Relative Effects of Feedback Frequency and Specificity of Eco-IVIS on Fuel Efficiency and Workload (에코 드라이빙 피드백 제공 빈도와 구체성이 연비와 작업부하에 미치는 효과)

  • Lee, Kyehoon;Cho, Hangsoo;Oah, Shezeen;Moon, Kwangsu
    • Journal of the Korean Society of Safety
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    • v.30 no.6
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    • pp.132-138
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    • 2015
  • This study examined the relative effects of feedback frequency and specificity of Eco-IVIS(eco in-vehicle information system) on the fuel-efficiency and workload. Eighty participants randomly assigned into four experimental groups (high frequency/specific, high frequency/global, low frequency/specific, and low frequency/global feedback) and they drove 16.4Km motorway under the each feedback condition. The dependent variable were fuel efficiency and Drive Activity Load Index which measured participants' subjective ratings of driving workload. The results showed that high frequent feedback was more effective for increasing fuel-efficiency than low frequent feedback, however, there was no significant difference of fuel-efficiency between specific and global feedback. Although, overall DALI score was comparable among four experimental conditions, visual demand score was significant higher under the high frequent feedback condition than low frequent feedback.

Differential Effects of Subjective Evaluation for Attention and Situation Adaptability on Driving Mobility as a Function of Driver's Age: Moderating Effect of Motivation (연령대에 따른 주관적 주의능력과 외부환경 적응능력이 운전이동성에 미치는 영향에서의 차이: 동기특성의 조절효과)

  • Jaesik Lee;Mijung Joo;Jung Ho Kim;Won Young Lee;Jun Beom Ryu;Ju Seok Oh
    • Korean Journal of Culture and Social Issue
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    • v.21 no.3
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    • pp.457-479
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    • 2015
  • This study investigated the differential effects of subjective evaluation for attention and situation adaptability, and motivation on driving mobility as a function of driver's age. The results can be summarized as followings. First, subjective capability evaluation tended to decrease as the drivers' age increased, and lower evaluation for situation adaptability seemed to be recognized earlier than attentional ability in middle-aged drivers. Second, although subjective evaluation for attentional ability predicted positively driving mobility of all age groups, but only subjective evaluation for situation adaptability predicted positively driving mobility of older drivers. Third, among motivational elements, BAS predicted positively driving mobility of young and middle-aged driviers, whereas BIS predicted positively driving mobility of older drivers. Finally, middle-aged drivers tended show increased driving mobility when their attentional ability score and BAS were high, whereas older drivers showed lowest level of driving mobility when their situation adaptability score and BIS were low. These results suggest importance of integrated consideration for drivers' subjective evaluation for attention and situation adaptability, and motivation to understand characteristics of driving mobility in different age groups.

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A study on the possibility of using dual task performance as a screening test for driving ability of elderly drivers (노인운전자 운전능력 선별검사로서 이중과제수행의 활용 가능성 연구)

  • Shin, Su-Jung
    • Journal of Convergence for Information Technology
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    • v.11 no.4
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    • pp.161-167
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    • 2021
  • This study was conducted to identify the relationship between the dual task performance and driving behavior of the elderly driver in order to identify whether the dual task can be utilized as a test to screen the driving ability of the elderly driver. We surveyed general information and driving-related information for 32 normal elderly drivers, and evaluated Y-DuCog(Yonsei-Dual task Cognitive screening) and the K-DBQ (Korean-Driving Behavior Questionnaire). As a result of the study, the performance of the dual task using the pegboard task and the animal name speaking showed a significant correlation with the score of the violation domain of K-DBQ. With this study, it was possible to confirm the possibility as a test for discrimination of driving ability.

Statistical Discriminant Analysis on the Driving Ability of the Brain-injured

  • Kim, Jae-Hee;Kim, Jeong-A
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.1
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    • pp.19-31
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    • 2005
  • Brain injured patients who had the driver's license before the injury of the brain were tested with the newly developed tool CPAD by Hangyang Medical School and the National Rehabilitation Center. The CPAD contains many variables to measure the ability of driving. Also for each patient the American standard CBDI score was measured and the result was compared with the CPAD results. Of interest is to classify the patients as pass, border, fail group after the CPAD test. To derive the discriminant functions with the group information based on CBDI, parametric/nonparametric and multivariate/univariate discriminant analysis was performed and discussed.

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Effects of Traffic Signals with a Countdown Indicator: Driver's Reaction Time and Subjective Satisfaction in Driving Simulation

  • Chang, Joonho;Jung, Kihyo
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.5
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    • pp.459-466
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    • 2017
  • Objective: This study examined two traffic signals with a countdown indicator in terms of driver's reaction time and subjective satisfaction score and their performance was compared with a standard traffic signal in driving simulation. Background: Dilemma zone is created when a traffic light changes at intersections. It often pushes drivers to rush in urgent and premature decision making whether to go or stop and thus induces unnecessary mental load among drivers, which may lead to sudden conflicts with following vehicles at intersections. Method: Forty college students (male: 20, female: 20) participated in this driving simulation study. Three traffic signals were employed: (1) standard traffic signal; (2) countdown-separated signal; and (3) countdown-overlaid signal. The countdown-separated and countdown-overlaid signals were designed to inform drivers of the remaining time of a green light before tuning to an amber light. Reaction times (sec) and satisfaction scores (7-point scale) for the two signals with a countdown indicator were compared with those for the standard traffic signal. Results: Reaction times of the countdown-separated (0.49 sec) and countdown-overlaid (0.43 sec) signals were significantly shorter than that of the standard signal (0.67 sec). Satisfaction scores of the countdown-separated (5.3 point) and countdown-overlaid (5.6 point) signals were greater than that of the standard signal (3.8 point). Lastly, the countdown-overlaid signal showed better performance than the countdown-separated signal, but their differences in reaction time (0.06 sec) and satisfaction score (0.3 point) were small. Conclusion: Traffic signals with a countdown indicator can improve drivers' reaction time and satisfaction score than the standard traffic signal. Application: Traffic signals with a countdown indicator will be useful for reducing the length of dilemma zone at intersections, by allowing drivers to predict the remaining time of a green light.

Development of a Workload Assessment Index Based on Analyzing Driving Patterns (운전자 주행패턴을 반영한 작업부하 평가지표 개발)

  • KIM, Yunjong;LEE, Seolyoung;CHOI, Saerona;OH, Cheol
    • Journal of Korean Society of Transportation
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    • v.35 no.6
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    • pp.545-556
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    • 2017
  • Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

Driving Performance Evaluation Using Bio-signals from the Prefrontal Lobe in the Driving Simulator

  • Kim, Young-Hyun;Kim, Yong-Chul
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.2
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    • pp.319-325
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    • 2012
  • Objective: The aim of this study was to develop the assistive device for accelerator and brake pedals using bio-signals from the prefrontal lobe in the driving simulator and evaluate its performance. Background: There is lack of assistive devices for the driving in peoples with disabilities in Korea. However, if bio-signals and/or brain waves are used at driving a car, the people with serious physical limitations can improve their community mobility. Method: 15 subjects with driver's license participated in this study for experiment of driving performance evaluation in the simulator. Each subject drove the simulator the same course 10 times in three separated groups which use different interface controllers to accelerate and brake: (1) conventional pedal group, (2) joystick group and (3) bio-signal group(horizontal quick glance of the eyes and clench teeth). All experiments were recorded and the driving performances were evaluated by three inspectors. Results: Average score of bio-signal group for the driving in the simulator was increased 3% compared with the pedal group and was increased 9% compared with the joystick group(p<0.01). The subjects using bio-signals was decreased 44% in number of deduction compared with others because the device had the built-in modified cruise control. Conclusion: The assistive device for accelerator and brake pedals using bio-signals showed significantly better performance than using general pedal and a joystick interface(p<0.01). Application: This study can be used to design adaptive vehicle for driving in people with disabilities.

Development of a driver's emotion detection model using auto-encoder on driving behavior and psychological data

  • Eun-Seo, Jung;Seo-Hee, Kim;Yun-Jung, Hong;In-Beom, Yang;Jiyoung, Woo
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.35-43
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    • 2023
  • Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.