• Title/Summary/Keyword: Human driving behavior

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운전자 주행 특성 파라미터를 고려한 지능화 차량의 적응 제어 (Driver Adaptive Control Algorithm for Intelligent Vehicle)

  • 민석기;이경수
    • 대한기계학회논문집A
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    • 제27권7호
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    • pp.1146-1151
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    • 2003
  • In this paper, results of an analysis of driving behavior characteristics and a driver-adaptive control algorithm for adaptive cruise control systems have been described. The analysis has been performed based on real-world driving data. The vehicle longitudinal control algorithm developed in our previous research has been extended based on the analysis to incorporate the driving characteristics of the human drivers into the control algorithm and to achieve natural vehicle behavior of the adaptive cruise controlled vehicle that would feel comfortable to the human driver. A driving characteristic parameters estimation algorithm has been developed. The driving characteristics parameters of a human driver have been estimated during manual driving using the recursive least-square algorithm and then the estimated ones have been used in the controller adaptation. The vehicle following characteristics of the adaptive cruise control vehicles with and without the driving behavior parameter estimation algorithm have been compared to those of the manual driving. It has been shown that the vehicle following behavior of the controlled vehicle with the adaptive control algorithm is quite close to that of the human controlled vehicles. Therefore, it can be expected that the more natural and more comfortable vehicle behavior would be achieved by the use of the driver adaptive cruise control algorithm.

실시간 운전 특성 모니터링 시스템을 위한 차량 환경 개발 (Development of Vehicle Environment for Real-time Driving Behavior Monitoring System)

  • 김만호;손준우;이용태;신승헌
    • 대한인간공학회지
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    • 제29권1호
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    • pp.17-24
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    • 2010
  • There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

Active learning 기반 운전자 행동 모방 학습 기법 연구 (A Study on a Driving Behavior Imitation Learning Method Based on Active Learning)

  • 황카이스;문명운;박지선;성연식;조경은
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2019년도 춘계학술발표대회
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    • pp.485-486
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    • 2019
  • Simulated driving behavior is an important aspect of realistic simulation systems. To simulate natural driving behavior, this paper proposes an imitation learning method based on active learning that combines demonstration and experience. Driving demonstrations are collected from human drivers in a driving simulator. A driving behavior policy is learned from these demonstrations. The driving demonstration dataset is augmented with new demonstrations that the original demonstrations did not contain, in the form of behaviors from another driving behavior policy learned from experience. The final driving behavior policy is learned from an augmented demonstration dataset.

운전행동 분석을 통한 위험운전행동에 관한 연구 (A Study on the Dangerous Driving Behaviors by Driver Behavior Analysis)

  • 서소민;김명수;이창희
    • 한국ITS학회 논문지
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    • 제14권5호
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    • pp.13-22
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    • 2015
  • 최근 교통사고 주요 원인인 인간행동(인적요인)에 대해 관심이 높아졌으며 운전행동분석 도구인 DBQ(Driver Behavior Questionnaire)를 활용한 운전행동(Driving Behavior)에 관한 연구가 활발히 진행되고 있다. 국내에서 진행된 선행연구는 분석대상이 연구원이나 군 공무원으로 한정되며 분석방법은 요인분석 및 회귀분석을 통해 이루어졌다. 이에 본 연구에서는 일반운전자의 운전행동이 위험운전에 미치는 영향요인을 파악하고 이들의 영향관계를 규명하고자 한다. 연구의 범위는 운전경력이 있는 일반운전자를 대상으로 DBQ설문을 실시하여 300부의 유효 표본수를 분석하였으며, 선행연구 고찰을 통해 교통사고의 주요 요인을 DBQ에서 측정가능한 'Lapse, Mistake, Violation' 세 가지속성으로 도출하고 구조방정식 모형을 통한 위험운전행동 모형을 구축하였다. 또한, 위험운전군별 차이를 확인하기 위하여 다중집단분석을 활용하였다. 분석결과 첫째, 'Lapse, Mistake, Violation 요인은 위험운전행동에 영향을 미칠 것이다'라는 가설검증 결과 모든 요인의 통계적 유의성이 확인되었다. 위험운전행동에 미치는 영향정도는 Violation 0.464, Lapse 0.383, Mistake 0.158 순으로 나타났으며 영향을 가장 많이 미치는 요인이 Violation으로 분석되었다. 둘째, 'Lapse, Mistake, Violation 요인이 위험운전행동에 미치는 영향은 위험군에 따라 다를 것이다'라는 가설검증 결과 Lapse 요인이 위험운전행동에 미치는 영향력이 차이가 있는 것으로 분석되었다. 본 연구결과는 위반행동 Violation과 부주의한 실수 Lapse를 고려한 교통사고 예방 프로그램 및 교육도입에 기초자료로 활용 가능할 것이다.

운전자 주행 특성을 고려한 차량 적응 순항 제어기 설계 (A Vehicle Adaptive Cruise Control Design in Consideration of Human Driving Characteristics)

  • 구자성;이경수
    • 한국자동차공학회논문집
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    • 제14권2호
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    • pp.32-38
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    • 2006
  • A vehicle adaptive cruise control strategy based on human drivers' driving characteristics has been investigated. Human drivers driving characteristics have been analyzed using vehicle test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would reduce the workload of the human driver. Vehicle following characteristics of the cruise controlled vehicle have been compared to real-world driving radar sensor data of human drivers using a validated vehicle simulator. and compare nominal cruise control and adaptive cruise control.

운전자 설문을 통한 자동차 운전자의 실수 확률 추정 (Estimation of Car Driver Error Probabilities Through Driver Questionnaire)

  • 이재인;임창주
    • 한국안전학회지
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    • 제22권1호
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    • pp.61-66
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    • 2007
  • Car crashes are the leading cause of death for persons of every age. Specially, human-related factor has been known to be the primary causal factor of such crashes than vehicle-and environmental-related factors. There are various studies to analyze driver's behavior and characteristics in driving for reducing the car crashes in many areas of car engineering, psychology, human factor, etc. However, there are almost no studies which analyze mainly the human errors in driving and estimate their probabilities in terms of human reliability analysis. This study estimates the probability of human error in driving, i.e. driver error probability. First, fifty driver errors are investigated through DBQ (Driver Behavior Questionnaire) revision and the error likelihoods in driving are collected which are judged by skillful drivers using revised DBQ. Next, these likelihoods are converted into driver error probabilities using the results that verbal probabilistic expressions are changed into quantitative probabilities. Using these probabilities we can improve the warning effects on drivers by indicating their driving error likelihoods quantitatively. We can also expect the reduction effects of car accident through controlling especially dangerous error groups which have higher probabilities. Like these, the results of this study can be used as the primary materials of safety education on drivers.

A Vehicle Stop-and-Go Control Strategy based on Human Drivers Driving Characteristics

  • Yi Kyongsu;Han Donghoon
    • Journal of Mechanical Science and Technology
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    • 제19권4호
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    • pp.993-1000
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    • 2005
  • A vehicle cruise control strategy designed based on human drivers driving characteristics has been investigated. Human drivers driving patterns have been investigated using vehicle driving test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver. Vehicle following charac­teristics of the cruise controlled vehicle have been investigated using real-world vehicle driving test data and a validated simulation package.

HUMAN-CENTERED DESIGN OF A STOP-AND-GO VEHICLE CRUISE CONTROL

  • Gu, J.S.;Yi, S.;Yi, K.
    • International Journal of Automotive Technology
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    • 제7권5호
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    • pp.619-624
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    • 2006
  • This paper presents design of a vehicle stop-and-go cruise control strategy based on analyzed results of the manual driving data. Human drivers driving characteristics have been investigated using vehicle driving data obtained from 100 participants on low speed urban traffic ways. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver under low speed stop-and-go driving conditions. Vehicle following characteristics of the cruise controlled vehicle have been investigated using a validated vehicle simulator and real driving radar sensor data.

운전자의 정서가 운전행동에 미치는 영향에 관한 연구: 운전스트레스 대처행동을 중심으로 (A Study on Effects of the Driver's Emotion on the Driving Behavior)

  • 권민정;오영태
    • 대한교통학회지
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    • 제31권6호
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    • pp.34-42
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    • 2013
  • 교통사고의 원인은 크게 차량요인, 도로환경요인, 인적요인으로 구성되는데 과거에 비해 비약적으로 발전한 기술로 인하여 현재는 교통참가자들의 교통행동이 가장 중요한 원인으로 주목받고 있다. 최근 활발하게 연구가 이루어지고 있는 정서는 인간의 판단과 행동결정에서 그 역할이 중요시 되고 있다. 이에 운전자가 운전행동을 판단하고 결정할 때에도 정서가 영향을 줄 것으로 예상되며 운전자의 정서가 운전행동에 어떠한 영향을 주는지 밝혀내는 것이 본 연구의 목적이다. 분석결과 긍정적 정서는 운전행동에 큰 영향을 주지 않지만 부정적 정서의 경우 안전운전 요인 및 여유운전 요인과는 부적(-) 상관관계를, 난폭운전 요인 및 법규위반 요인과는 강한 정적(+) 상관관계를 갖는 것으로 나타났다. 또한 회귀분석을 통해 적합도가 가장 높은 2차 함수 모형을 구축하였다. 본 연구는 운전자의 정서와 운전행동과의 관계를 확인했다는 점에서 의의가 있으며 교통사고를 줄이기 위한 정책을 수립하고 결정할 때뿐만 아니라 효과적인 운전자 교통안전교육의 기초연구로서 의미가 있다고 할 수 있다.

도심 정체 상황에서의 자율주행 차선 변경 알고리즘 개발 및 평가를 위한 실도로 데이터 기반 시뮬레이션 환경 개발 (Human Driving Data Based Simulation Tool to Develop and Evaluate Automated Driving Systems' Lane Change Algorithm in Urban Congested Traffic)

  • 서다빈;채흥석;이경수
    • 자동차안전학회지
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    • 제15권2호
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    • pp.21-27
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    • 2023
  • This paper presents a simulation tool for developing and evaluating automated driving systems' lane change algorithm in urban congested traffic. The behavior of surrounding vehicles was modeled based on driver driving data measured in urban congested traffic. Surrounding vehicles are divided into aggressive vehicles and non-aggressive vehicles. The degree of aggressiveness is determined according to the lateral position to initiate interaction with the vehicle in the next lane. In addition, the desired velocity and desired time gap of each vehicle are all randomly assigned. The simulation was conducted by reflecting the cognitive limitations and control performance of the autonomous vehicle. It was possible to confirm the change in the lane change performance according to the variation of the lane change decision algorithm.