• 제목/요약/키워드: Human driving data

검색결과 147건 처리시간 0.026초

실도로 주행 데이터 기반 차선변경 주행 특성 분석 (Lane Change Driving Analysis based on Road Driving Data)

  • 박종철;채흥석;이경수
    • 자동차안전학회지
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    • 제10권1호
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    • pp.38-44
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    • 2018
  • This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

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.

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.

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.

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.

주행 시뮬레이터를 이용한 차량 안정성 제어기의 성능 검증 (Evaluation of Vehicle Stability Control System Using Driving Simulator)

  • 정태영;이건복;이경수
    • 한국자동차공학회논문집
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    • 제12권4호
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    • pp.139-145
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    • 2004
  • This paper presents human-in-the-loop evaluations of vehicle stability control(VSC) system using a driving simulator. A driving simulator which contains full vehicle nonlinear model is evaluated by using actual vehicle test data on the same driving conditions. Braking control inputs for Vehicle Stability Control system have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. Closed-loop simulation results at realistic driving situations have shown that the proposed controller reduces driving effort of a driver and enhances stability of a vehicle.

HUMAN-IN-THE-LOOP EVALUATION OF A VEHICLE STABILITY CONTROLLER USING A VEHICLE SIMULATOR

  • Chung, T.;Kim, J.;Yi, K.
    • International Journal of Automotive Technology
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    • 제5권2호
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    • pp.109-114
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    • 2004
  • This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) system using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

최적예견 제어 기법을 이용한 운전자 조향 모델의 개발 및 검증 (Development and Validation of A Finite Optimal Preview Control-based Human Driver Steering Model)

  • 강주용;이경수;노기한
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.855-860
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    • 2007
  • This paper describes a human driver model developed based on finite preview optimal control method. The human driver steering model is constructed to minimize a performance index which is a quadratic form of lateral position error, yaw angle error and steering input. Simulation studies are conducted using a vehicle simulation software, Carsim. The Carsim vehicle model is validated using vehicle test data. In order to validate the human driving steering model, the human driver steering model is compared to the driving data on a virtual test track(VTT) and the actual vehicle test data. It is shown that human driver steering behaviors can be well represented by the human driver steering model presented in this paper

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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.

자율주행 차량의 실도로 주행을 위한 안전 시나리오 기반 인간중심 시스템 성능평가 (Toward Real-world Adoption of Autonomous Driving Vehicle on Public Roadways: Human-Centered Performance Evaluation with Safety Critical Scenarios)

  • 국윤영;이경수
    • 자동차안전학회지
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    • 제15권2호
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    • pp.6-12
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    • 2023
  • For the commercialization and standardization of autonomous vehicles, demand for rigorous safety criteria has been increased over the world. In Korea, the number of extraordinary service permission for automated vehicles has risen since Hyundai Motor Company got its initial license in March 2016. Nevertheless, licensing standards and evaluation factors are still insufficient for operating on public roadways. To assure driving safety, it is significant to verify whether or not the vehicle's decision is similar to human driving. This paper validates the safety of the autonomous vehicle by drawing scenario-based comparisons between manual driving and autonomous driving. In consideration of real traffic situations and safety priority, seven scenarios were chosen and classified into basic and advanced scenarios. All scenarios and safety factors are constructed based on existing ADAS requirements and investigated via a computer simulation and actual experiment. The input data was collected by an experimental vehicle test on the SNU FMTC test track located at Siheung. Then the offline simulation was conducted to verify the output was appropriate and comparable to the manual driving data.