intelligence & interaction lab - kookmin

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Intelligence and Interaction Lab Kookmin University Intelligence & Interaction Lab 지능 인터랙션 실험실 Graduate School of Automotive Engineering Kookmin University Seoul, Korea

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Page 1: Intelligence & Interaction Lab - Kookmin

Intelligence and Interaction Lab Kookmin University

Intelligence & Interaction Lab 지능 인터랙션 실험실

Graduate School of Automotive EngineeringKookmin University

Seoul, Korea

Page 2: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

LEE, Sang Hun

Education 1993 PhD Seoul National University, Mech. Eng. 1988 MS Seoul National University, Mech. Eng. 1993 BS Seoul National University, Mech. Eng.

Experience 1996 ~ Present Kookmin University, Professor 1999 Univ. of Washington, Visiting Scholar 1996 Advanced Engineering Institute, Researcher 1993 ~ 1995 SindoRicoh Co., Researcher

Research Interest Intelligent Human-Vehicle Systems and Interaction CAD and Human CAD for Automotive Design and Manufacturing Human-Machine Interaction (HMI) and HCI Machine Learning, Computer Graphics

Home Page Lab:http://ii.kookmin.ac.kr or http://cad.kookmin.ac.kr

Page 3: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Facilities

Softwares Driving Simulation SW

PreScan, OpenDS, UC-win/Road

CAD/CAM CATIA, NX, Tecnomatics,

RapidForm Human CAD/CAE

AnyBody, Jack

Hardwares Driving Simulator

Kia K7

Driving Simulator

CATIA AnyBody

UC-win/Road

Page 4: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Research Areas

Human-Vehicle Systems and Interaction Intelligent Driver-Vehicle Systems and User Interface Human-Vehicle Interaction Design and Engineering Applications of Machine Learning Technology

Digital Human Modeling and Simulation

Page 5: Intelligence & Interaction Lab - Kookmin

Intelligence and Interaction Lab Kookmin University

Driving State Driver State Warning Device Control Autonomous Driving

Driver Intent Inference using Machine Learning Algorithms (1/4)

Background• Accidents due to carelessness, drowsiness and inexperienced

driving of the driver• Discrepancies between the various driving conditions, driver

intention and advanced driver assistance systems.• Increase in demand for a wide range of human-oriented

context-aware services.

Objective• Development of an active driver assistance system to respond

appropriately through a prediction of driver intention and traffic condition.

Approach• Generating predictive models for driving condition and driving

conditions using machine learning

Machine Learning

Vehicle

Driver

Page 6: Intelligence & Interaction Lab - Kookmin

Intelligence and Interaction Lab Kookmin University

Essential Features

DriverHead Motion

Pupil Movement

Vehicle

Throttle Position

RPM

Speed

Longitudinal Acceleration

Steering Angle

Steering Velocity

Lateral Speed

Lateral Acceleration

Yaw Rate

Heading

Road

Time to Cross LaneLine

Offset from lanecenter

Surrounding Vehicle

Distance

Relative Speed

Time to Collision

ETC ː

DataAcquisition

Driver Intent Inference using Machine Learning Algorithms (2/4)

Page 7: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Machine Learning Tool

Machine Learning Algorithm

Neural network

Support Vector Machine

Bayesian Network

···

Data Analysis, Model Design Pattern Recognition

Autonomous Driving

Driving State (Lane Change, Stop, Go, Turn, …)

Device Control

Driver StateWarning

Driver Intent Inference using Machine Learning Algorithms (3/4)

Page 8: Intelligence & Interaction Lab - Kookmin

Intelligence and Interaction Lab Kookmin University

DisadvantagesIt’s hard to acquire the information of gaze

area. Too expensive

It’s hard to sustain the zero point during driving.

Essential Features

Driver

Head Motion

Pupil Movement(Stare area information)

Vehicle

Throttle Position

RPM

Speed

Longitudinal Acceleration

Steering Angle

Steering Velocity

Lateral Speed

Lateral Acceleration

Yaw Rate

Heading

Road

Time to Cross LaneLine

Offset from lanecenter

Surrounding Vehicle

Distance

Relative Speed

Time to Collision

ETC ː

SMI ETG DikablisKinect & Remodeled Webcam

OpenDS & Tobii & Faceshift & Structure sensor

Driver Intent Inference using Machine Learning Algorithms (4/4)

Page 9: Intelligence & Interaction Lab - Kookmin

Intelligence and Interaction Lab Kookmin University

HMI for Multi-levels of Autonomous Vehicle(1/3)

Background• Spread autonomous vehicle due to various advanced driver

assistance systems(ADAS)• Driver maneuverability difficulties in the absence of a

unified HMI for autonomous vehicle (by SBD research 2013)

• Interface complexity, disconnection Driver is experiencing various confusion (by SBD research 2013)

Objective• To develop new driver interfaces for an autonomous vehicle

for effective interaction between intelligent system and driver.

Approach• Propose an driver-centric interface design approach• Perform driver-in-the-loop experiments

Operation degrees, Mode confusion when using systems, etc.

Page 10: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Driver interface design & engineering• Design driver-centric interfaces• Develop mode transition chart consisting of various ADAS• Apply formal verification approach

HMI for Multi-levels of Autonomous Vehicle(2/3)

Page 11: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Driver-in-the-loop experiment• Driver situation awareness, mode confusion evaluation• Design experimental roads and scenario using PreScan and

Matlab&Simulink PreScan: supporting development of driver assistance systems

and intelligent vehicle systems by providing an emulation function of various sensors (using Matlab & Simulink)

Absence: Eye track, Sound, Slow simulation

Dramoni (http://www.trywin.co.jp/item_detail/item_000016.html)

PreScan

Matlab & Simulink

HMI for Multi-levels of Autonomous Vehicle(3/3)

Page 12: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Wheel Gesture Interaction Design

세부기능조절(ex :볼륨증가)

초기화면Back기능(ex :OFF)

초기 화면

메뉴 선택(ex :라디오)

[ 휠제스처 조작프로세스 ]

Page 13: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Human-Vehicle Interaction Design & Analysis on Virtual Human-Product-Environment System

Page 14: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Virtual Driver Based on ACT-R

Extension of ACT-R Visual and Motor Modules Comparison of Experimental and Simulation Results

Human Experiment ACT-R Simulation

Validation of Virtual Driver Development of Virtual Driver

Page 15: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

IntegratedHuman CAD

System

CAEMADYMO

(Crash Safety)

CAELifeMOD

(Biomechanics)

DigitalHuman

DigitalProduct

Parametric Human Modeling

Motion Simulation

Ingress/Egress Analysis

Integrated Human CAD/CAE System

Page 16: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Human-centered Virtual Design and Analysis Process

Virtual Prototype

Motion & EMG Data Capture

Motion Reconstruction Biomechanical

Analysis

Ergonomic Evaluation

DB

Digital Human Generation

Motion Generation

• Motion• Force• EMG

Page 17: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Human CAD

18

SimulationDMU of Vehicle + Digital Human

DMU of Vehicle

Tasks

Digital Manikin

-Sit-Hold Steering Wheel-Depress Pedal-Etc.

Reach/Motion Analysis

Vision Analysis

Comfort Assessment

Package Layout

Page 18: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Virtual Integrated Development Environment (VIDE) for Green Car Parts

Page 19: Intelligence & Interaction Lab - Kookmin

Kookmin UniversityIntelligence and Interaction Lab

Projects (selected)

운전자 상태와 주행 환경 분석을 통해 안전과 편의를 제공하는 Connectivity 기반의 개인맞춤 지능형 통합 Cockpit 모듈 개발 (지식경제부, 2013 ~ 2014)

제품과 인체의 통합 모델을 바탕으로 한 스포츠용품의 가상 설계 및 시험 프레임웍의 개발 (한국연구재단, 2013 ~ 현재)

근신경학적 퇴행 지연을 위한 디지털 인체 모델 기반 기반 통합 운동 시스템의 가상 설계 및시험 프레임웍 개발 연구 (2013 ~ 현재)

감성기반 지능형 자동차 인터랙션에 대한 공학-디자인 융합 연구 (한국연구재단, 2013) 인간친화적인 차량설계를 위한 인체동작 시뮬레이션 및 안락도 평가기술의 개발 (산학협동

재단, 2011~2012 ) 그린카 부품 상용화지원을 위한 가상개발환경(VIDE) 개발 (지식경제부, 2010~2012) 지식기반 3차원 금형설계 자동화 시스템 개발 (서울시 산학연, 2009~2011) 인간중심설계를 위한 제품 및 인체의 통합 CAD/CAE 시스템의 개발 (한국과학재단,

2008~2011) 지식기반 설계기술 개발 (GM대우 자동차, 2006~2008) 지능형 금형설계 시스템 (산업자원부, 2006~2007) 충돌 안전 해석을 위한 솔리드 중립면 생성 프로그램 (현대모비스, 2006~2007) 인간 친화적 미래형 자동차를 위한 인체 모델링과 시뮬레이션 시스템 개발 (교육인적자원부

/산업자원부/노동부, 2005~2007)