Collision Reconstruction Methodologies Volume 1: Collision

Collision Reconstruction Methodologies

Volume 1: Collision Documentation

Warrendale, Pennsylvania, USA

v©2019 SAE International

contents

Introduction xiii

C H A P T E R 1

A Video Tracking Photogrammetry Technique to Survey Roadways for Accident Reconstruction 1

Background 1Introduction 2Video Tracking Photogrammetry 4

Scene Surveying 4

Setting Up the Video Take 5

Taking the Video 5

Tips 5

Processing the Data 6

Case Studies 7Flat Highway 7

Road Signs and Telephone Poles 7

Rolling Highway 9

Comparison of Survey Accuracy for Road Curvature 12

Comparison of Survey Accuracy for Road Profile 12

Residential Roads 12

Future Development 12Conclusion 14References 14

C H A P T E R 2

A Three-Dimensional Crush Measurement Methodology Using Two-Dimensional Photographs 15

Introduction 15Previous Research Studies 16Methodology 17

vi Contents

Procedure 18Step One: Photograph Selection 18

Step Two (Part One): Wireframe Model Acquisition 19

Step Two (Part Two): Model/Photograph Alignment 19

Step Three: Vertices Displacement (“Deforming” The Model) 20

Selected Case Studies 20Case Study No. 1 20

Methodology 20

Case Study No. 1 Results 22

Case Study No. 2 22

Methodology 23

Case Study No. 2 Results 24

Discussion 24Conclusion 25Acknowledgments 25References 26Appendix A. Case Study No. 1: Comparison of Crush Measurements Using Various Methodologies 29Appendix B. Case Study No. 2: Comparison of Crush Measurements Using Various Methodologies 30

C H A P T E R 3

Using Particle Image Velocimetry for Road Vehicle Tracking and Performance Monitoring 31

Introduction 32Purpose 32

Background 32

Literature Review 33

Overview 34

Mathematical Basis for DPIV 34Description of Vehicle Kinematics 36Preliminary Testing 38Bounds of Performance 39Experimental Procedures 40

Description of Systems 40

Calibration 40

Modifications to OpenPIV 40

Data Collection 40

Straight-Line Driving Test Results 41

Contents vii

Analysis of Data 42Omission of Outliers 42

Least Squares Analysis 43

Comparison of Analysis Techniques 44

Sources of Uncertainty 44Conclusions 45References 45

C H A P T E R 4

Benefits and Methodology for Dimensioning a Vehicle Using a 3D Scanner for Accident Reconstruction Purposes 47

Introduction 48Methodology for Dimensioning a Vehicle 49

Scanner Setup Prior to Inspection Trip 49

Scanner Setup at Inspection 50

Scanning a Vehicle 51

Post Processing the Scanner Data 52

Reconstruction Case Studies 55Case 1: A Roof Deformation Case on a Small Sport Utility Vehicle 55

Case 2: Collision Between a Motorcycle and Towed Trailer 56

Case 3: Intersectional Collision Case Involving Two Vehicles 57

Case 4: Damage Documentation on a UTV 59

Case 5: Seat Belt and Seat Movement Investigation 60

Discussion 60Conclusions 61References 62Acknowledgments 62

C H A P T E R 5

The Accuracy of Photo-Based Three-Dimensional Scanning for Collision Reconstruction Using 123D Catch 63

Introduction 64Crush Jigs 64

Plumb Line Tracing 64

viii Contents

Total Station Survey 64

Laser Scanning 65

Coordinate Measuring Machines 65

Traditional Photogrammetry 65

Photo-Based 3D Scanning 66

Photo-Based 3D Scanning Theory 66

Photo-Based 3D Scanning Software 67

Purpose 67

Method 67Vehicle Preparation 67

Total Station Measurements 69

Traditional Photogrammetry Measurements 69

Photo-Based 3D Scanning 70

Data Analysis 71

Results 72Comparison between Total Station and Photo-Based 3D Scanning 72

Comparison between Traditional Photogrammetry and Photo-Based 3D Scanning 72

Discussion 73Measurement Deviation 73

Strengths of Photo-Based 3D Scanning 73

Limitations of Photo-Based 3D Scanning 74

Summary/Conclusions 75References 75

C H A P T E R 6

Applying Camera Matching Methods to Laser-Scanned Three-Dimensional Scene Data with Comparisons to Other Methods 79

Introduction 80Photogrammetry Methods Used 81

Photogrammetry Software 81

Photogrammetry Using Point Cloud Data 82

Photograph Rectification of Point Cloud Data 83

Camera Matching to Point Cloud Data 83

Photogrammetry Using 3D Scanner Data 84The Method of Virtual Camera Matching to a Scene 84

Applying the Virtual Camera Matching Method to a Complex Crash on Sloped Terrain 87

Accuracy Comparison for the Staged Collision 89

Contents ix

Photograph Considerations for Camera Matching Photogrammetry 93Summary/Conclusions 94References 95Acknowledgments 95Appendix 96

C H A P T E R 7

Assessment of the Accuracy of Google Earth Imagery for Use as a Tool in Accident Reconstruction 107

Introduction 108Methodology 109Results 114Discussion 116Summary/Conclusions 117References 118Acknowledgments 118Appendix 119

C H A P T E R 8

A Quantitative Method for Accurately Depicting Still Photographs or Video of a Nighttime Scene Utilizing Equivalent Contrast 131

Introduction 132Contrast 133

Prior Methodologies 133

Methodology 134Overview 134

Testing 134

Results 136Calibrating for an Object that cannot be Seen 136

Calibrating for an Object that can be Seen 137

Discussion 138Conclusions 139

x Contents

References 140Conflict of Interest Statement 140

C H A P T E R 9

Evaluation of the Accuracy of Image-Based Scanning as a Basis for Photogrammetric Reconstruction of Physical Evidence 141

Introduction 142Underlying Concepts—Image-Based Scanning 143Advantages of Unmanned Aerial Vehicles 144Methodology 144Results 147Discussion and Conclusions 152References 152Appendix 154

Appendix A—Images of Photogrammetric Process 154

Appendix B—Comparison of Individual Reconstructed Points to FARO Scan Data 161

C H A P T E R 1 0

A Survey of Multiview Photogrammetry Software for Documenting Vehicle Crush 163

Introduction 164Methodology 165

3D Scanner Documentation 165

Photograph and Video Documentation 166


3D Scan Data Processing 168

Photogrammetric Data Processing 168

Scaling and Comparing the Point Clouds 169

Results 174Initial Software Evaluation 174

Camera Comparison 176

Photographs and Video Comparison 179

Software Evaluation Using Limited Photographs 181

Damaged and Undamaged Vehicle Comparison 184

Further Analysis: Photographs and Video Comparison 187

Contents xi

Summary/Conclusions 189References 191Acknowledgments 193Appendix 194

Appendix A Complete Photograph Sets by Camera 194

Appendix B Histograms of Photogrammetry Software Data Distance from LiDAR Data 202

Appendix C Histograms of Camera-Specific Photogrammetry Software Data Distance from LiDAR Data 204

Appendix D Histograms of Video-Based Photogrammetry Software Data Distance from LiDAR Data 206

Appendix E Histograms of Specific Photograph Amounts—Photogrammetry Software Data Distance from LiDAR Data 208

About the Author 211


Volume 2: Night Vision Study



contents

Introduction ix

C H A P T E R 1

Threshold Visibility Levels for the Adrian Visibility Model under Nighttime Driving Conditions 1

Introduction 1Methods 2

Data/Model Integration 2

Analysis 5

Results 6Discussion 9Conclusion 11References 11

C H A P T E R 2

Validation of Digital Image Representations of Low-Illumination Scenes 13

Introduction 13Low-Illumination Photography Methods 14Methods 17

Overview 17

Scene SetUp 17

Camera 17

Images 18

Contrast Charts 18

Displays and Printer 19

Calibrating the Display Devices 19

Image Processing 19

Image Size and Viewing Distance 20

vi Contents

Subjects 20

Experimental Procedure 20

Print Format 20

Computer Monitor/Projector 21

Ratings 21

Results 21Print Photographs 21

CRT-Displayed Photographs 21

Projector-Displayed Photographs 22

CRT vs. Projector 22

Discussion 22Conclusion 24References 24

C H A P T E R 3

Digital Camera Calibration for Luminance Estimation in Nighttime Visibility Studies 27

Introduction 27Background 28

Opto-Electronic Conversion Function 28

Color 30

Noise 30

Methods 31Equipment 31

Software 31

Scenes 31

Processing 32

Color Filter Array 32

Lights, Flats, Darks, and O�sets 33

Work Flow 34

Results 35Discussion 36Conclusion 38Acknowledgments 38References 38Definitions, Acronyms, Abbreviations 39Appendix 39

Contents vii

C H A P T E R 4

Simulating Headlamp Illumination Using Photometric Light Clusters 43

Introduction 43Background on Light Simulation 44Simulated Light Photometrics 45Creating a Photometric Light Cluster 48

Analyze Light Distribution 48

Project Quadrants at Distances 49

Converting Photo Plates to Mesh Objects 50

Determine Computer-Generated Light Source Locations 52

Create Projection Maps for Computer-Generated Light Sources 54

Valitation 55Discussion and Conclusions 56References 57Appendix A 59Appendix B 60Appendix C 60

C H A P T E R 5

Validation of High Dynamic Range Photography as a Tool to Accurately Represent Low-Illumination Scenes 61


Participants 63

Test Scene 63

Digital Photographs 64

Procedure 65

Analysis 66


viii Contents

C H A P T E R 6

Nighttime Videographic Projection Mapping to Generate Photo-realistic Simulation Environments 71

Introduction 72Background 72Baseline Video Footage Used for Comparison 73Testing the Methodology 78

a. Video Footage of Driving Environment 78

b. Geometry Data of the Driving Environment 78

c. Video Footage of Vehicles in Varying Conditions 79

d. Geometry Data of the Vehicles 79

e. Projection Mapping for a Computer Environment 80

f. Computer Visualization of Vehicles 80

g. Combining Environment and Vehicle Systems Together 81

h. Varying Parameters of Vehicle and Scene 82

Additional Scenarios 82Conclusion 84References 85Appendix 86

Appendix A 86

About the Author 95


Volume 3A: Photogrammetry



contents

Introduction xvii

V O L U M E 3 A — C H A P T E R 1

Determination and Verification of Equivalent Barrier Speeds (EBS) Using PhotoModeler as a Measurement Tool 1

Introduction 1Selection of Samples 2Photomodeler Procedure 2

Description of the Software 2

Description of a Generic PhotoModeler Procedure 3

Camera Calibration 3

Exemplar Modeling 4

Crushed Vehicle Modeling 6

EBS Determination 6Crush Coefficient Determination 7

Computing EBS 9

Bootstrapping 9Results 11

Within Subjects Design 11

Between Subjects Design 11

Bootstrapping 11

Conclusion 12References 12Appendix A 13Appendix B 15Appendix C 17Appendix D 22


New Algorithm for the Range Estimation by a Single Frame of a Single Camera 27

Introduction 28Principle of Range Estimation 28

vi Contents

Procedure of Range-Window Algorithm 31Preprocessing 31

Trinary Image 31

Binary Image 31

Process in a Single Window 33

Line Segmentation 33

Object Segmentation 33

Scoring and Best Object-in-Window Determination 33

Estimation of the Range 34

Application to Real Image 34Condition of Range-Window Algorithm 34

Measuring System 34

Measurement and Range Estimation 35

Results 35

Variety of Vehicles 35

Process of RWA 36

Vehicle Following Test 36

Discussion 41Range Limitation 41

Vehicle Model 41

Size of Range-Window 41

Object at Very Short Range 42

Applicable Road Condition 42

Conclusion 43 Acknowledgments 43References 43Appendix A: Scenario-A and Scenario-B 44


Use of Photogrammetry in Extracting 3D Structural Deformation/Dummy Occupant Movement Time History During Vehicle Crashes 47

Introduction 48Test Methods and Materials 49Results 51Conclusion 59

Contents vii

Acknowledgments 59References 59


Image Analysis of Rollover Crash Tests Using Photogrammetry 61

Introduction 61Approach 62

Processing Tools 62

Using 3D Modeler In Rollover Analysis 62

Procedure 63

Camera-Matching Photogrammetry 64

Setup 65

Analysis 65

Data Process 67

Results 69Discussion 71

Areas for Improvement 71

Accuracy Determination 72

Vehicle Kinematics 73

Conclusion 75Acknowledgment 75References 76


Security Needs for the Future Intelligent Vehicles 77

Introduction 78Secure Communications, Security Mechanisms, and Attack Types 79

Secure Communications 79

Security Mechanisms 79

Attack Types 79

Future Vehicle Systems 80Inter Vehicle Communications 80

Ad Hoc Networks 80

Vehicle Positioning systems 81

viii Contents

In-Vehicle Bus Systems 82

Vehicle Buses 82

Modules 82

Security Attacks 83Inter Vehicle Communications Attacks 83

Ad Hoc Networks 83

Vehicle Positioning Systems 84

In-Vehicle Bus System Attacks 84

Modules 85

Software Attacks 85

Hardware Attacks 85

Needs for Securing Vehicle Communication and Information 86Conclusion 87References 88


As-Assembled Suspension Geometry Measurement Using Photogrammetry 91

Introduction 91The Manual Measurement Process 93Evaluation of Extant Spatial Measurement Technologies 97A Photogrammetry-Based Measurement System 98

EOS Systems PhotoModeler Pro 5 98

Field Calibration 99

Subpixel Target Marking 99

Scale 99

Accuracy 99

Camera Settings 100

Field Calibration 100

Measurement Photographs 100

Targets 101Vector Rod-end Targets 101

Scale Bar 102

Wheel Surface Targets 102

Reference Targets 102

The Photogrammetry Process 103Verification 105Conclusions 106Acknowledgments 107References 107Appendix 108

Contents ix


Laser Tracker and Digital Photogrammetry's Merged Process for Large-Scale Rapid Scanning 111

Introduction 112Fuselage Measurements with the Laser Tracker and Digital Photogrammetry Merged Process 113Automated Measurements 113

Measuring Aircraft Structure 114

Current Laser Trackers Used in Production 114

Laser Tracker Performance 114

Improved Aircraft Structure Measurements 115Laser Tracker and Photogrammetry-Friendly “Combo Targets” 116

Laser Tracker and Photogrammetry Merged Metrology Performance 117

Large Area Rapid Scanning (Lars) 117Vertical Position Bar 117Current Boeing Experimental Examples 118Historical Quality Assurance Systems at Boeing 119Proposed New Standardized, Real-Time, Production-Monitored Analysis 120Conclusion 120Acknowledgments 120References 121Definitions, Acronyms, Abbreviations 121


The Accuracy of Photogrammetry vs. Hands-On Measurement Techniques Used in Accident Reconstruction 123

Introduction 124Method 125

Hands-On Measurement 126

Photogrammetry Measurement 127

Baseline Total Station Measurements 127

Results 129Discussion 134Summary/Conclusions 136

x Contents

References 136Acknowledgments 138Appendix A 139


Photogrammetric Measurement Error Associated with Lens Distortion 141

Introduction 142Background 142Testing Procedure 144Creating an Undistorted Image 144Manually Assessing Lens Distortion Coefficients in a Camera 146Sample Procedure 147Results of the Study 150Effect of Lens Distortion in Real-World Measurements 153Conclusions 155References 156Appendix A (Distortion Distance, per Camera, per Focal Length) 157Appendix B (Correction Coefficient Database) 192



Volume 3B: Photogrammetry



contents

Introduction xvii

V O L U M E 3 B — C H A P T E R 1

Close-Range Photogrammetry with Laser Scan Point Clouds 1

Introduction 2Test Methods and Data Acquisition 3Data Processing and Evidence Location 4

Digital Image Processing 4

Site Diagram 4

Analysis in Photomodeler 5

Analysis in Leica Cyclone 5

Error Analysis 7

Results 8Discussion 9Conclusions 11References 12


A Close-Range Photogrammetric Solution Working with Zoomed Images from Digital Cameras 13

Introduction 14Overview of Zoom-Dependent (Z-D) Analysis 16Illustrative Photogrammetric Study 16Z-D Calibration Procedure 17Small-Scale “Vehicle” Network Measurement of the Porsche 911 20Discussion of the Vehicle Z-D Networks 22Large-Scale Network Measurement of Natural Features in a Parking Lot Scene 25Scaling the Networks 26Discussion of Results 27

vi Contents

Small-Scale Projects 27

DSLR Cameras—Incident and Exemplar Z-D Calibrations 27

DSLR Cameras—Using EXIF Focal Length 27

PAS Cameras—Kodak C142—Incident and Exemplar Z-D Calibrations 27

PAS Cameras—Kodak C142—Using EXIF Focal Length 27

PAS Cameras—Kodak C142—Using FOOM Calibration 28

PAS Cameras—Nikon S510—Incident Z-D Calibrations 28

PAS Cameras—Nikon S510—Using EXIF Focal Length 28

PAS Cameras—Canon SD 1300 IS—Incident Z-D Calibration 28

PAS Cameras—Canon SD 1300 IS—Using EXIF Focal Length 28

Large-Scale Project 28

General Observations 29

Conclusions and Recommendations 30References 30


Four-Point Planar Homography Algorithm for Rectification Photogrammetry: Development and Applications 33


Geometry 35

Linear Map 36

Four Control Points 37

Conditioning 38

Four-Point Algorithm 40

Results 40Case Study 1 40

Discussion 44Conclusion 46References 46Acknowledgment 47Appendix 48

Appendix A 48

Case Study 2 48

Laboratory Data Study 50

Contents vii


Video Projection Mapping Photogrammetry through Video Tracking 55

Introduction 56Background 57Procedure 58Documenting the Accident Scene 59Processing and Tracking the Video Footage to Make a 3D Computer Model 61Projection Mapping From Video onto the Computer Model 63Evaluation of the Accuracy of Projection Mapping 64Conclusions 66References 67


Applying Camera Matching Methods to Laser-Scanned Three-Dimensional Scene Data with Comparisons to Other Methods 69

Introduction 70Photogrammetry Methods Used 71


Photogrammetry Using Point Cloud Data 72

Photograph Rectification of Point Cloud Data 73

Camera Matching to Point Cloud Data 73

Photogrammetry Using 3D Scanner Data 74The Method of Virtual Camera Matching to a Scene 74

Applying the Virtual Camera Matching Method to a Complex Crash on Sloped Terrain 77

Accuracy Comparison for the Staged Collision 79Photograph Considerations for Camera Matching Photogrammetry 83Summary/Conclusions 84References 85Acknowledgments 85Appendix 86

viii Contents


Accuracy of SUAS Photogrammetry for Use in Accident Scene Diagramming 97


Total Station Measurement 101

Photogrammetric Measurement 102

Results 105Discussion 105Summary/Conclusions 108References 108Acknowledgments 109Appendix 110

Appendix A: Measurement Data 110

Appendix B: Mock Accident Scene Diagrams 114

Appendix C: Mock Accident Scene Orthophotos 116


The Accuracy of an Optimized, Practical Close-Range Photogrammetry Method for Vehicular Modeling 119


Photogrammetry 121

Total Station 123

FaroArm 123

Data Comparison 123

Photogrammetry vs. Total Station 123

Photogrammetry vs. FaroArm 123

Results 124Photogrammetry vs. Total Station 124

Photogrammetry vs. FaroArm 125

Discussion 127Summary/Conclusions 128References 128Acknowledgments 129Appendix 130

Appendix A—Photographs used for Acura Photogrammetry vs. Total Station Model 130

Contents ix

Appendix B—Photographs used for Chrysler Photogrammetry vs. Total Station Model 131

Appendix C—Photographs used for VW Photogrammetry vs. Total Station Model 132

Appendix D—Photographs used for Acura Photogrammetry vs. Faroarm Model 133

Appendix E—Photogrammetry Data for Acura Photogrammetry vs. Total Station Model 134

Appendix F —Photogrammetry Data for Chrysler Photogrammetry vs. Total Station Model 137

Appendix G—Photogrammetry Data for VW Photogrammetry vs. Total Station Model 140

Appendix H—Photogrammetry Data for Acura Photogrammetry vs. Faroarm Model 143


Evaluation of the Accuracy of Image-Based Scanning as a Basis for Photogrammetric Reconstruction of Physical Evidence 147

Introduction 148Underlying Concepts—Image-Based Scanning 149Advantages of Unmanned Aerial Vehicles 150Methodology 150Results 153Discussion and Conclusions 158References 158Appendix 160

Appendix A—Images of Photogrammetric Process 160

Appendix B—Comparison of Individual Reconstructed Points to FARO Scan Data 167


An Evaluation of Two Methodologies for Lens Distortion Removal when EXIF Data is Unavailable 169

Introduction 170Background 171Methodology 173

Cameras 173

x Contents

Physical Study Site Layout and Documentation 173

Automatic, Library-Based Method 176

Straight-Line Method 177

Point Cloud Method 178

Analysis/Results 179Straight-Line Method: Radial Pixel Movement 179

Straight-Line Method: Photogrammetry 182

Point Cloud Method: Radial Pixel Movement 183

Point Cloud Method: Photogrammetry 183

Camera Locations 184

Conclusions 185References 186Acknowledgments 189Definitions/Abbreviations 189Appendix 190

Appendix A 190

Appendix B 194



Volume 4: Motorcycle Accident Reconstruction



contents

Introduction xiii

C H A P T E R 1

Technical Parameters for the Determination of Impact Speed for Motorcycle Accidents and the Importance of Relative Speed on Injury Severity 1

Introduction and Objectives 2Historical View on In-Depth Studies Describing the Injury Situation of Motorcyclists 3Possibilities of In-Depth Research 3Basis for Reconstruction 5Basis for Statistics 5Basis for the Study 5Kinematics of Motorcycle Accidents 6Collision and Injury Situations of Motorcyclists 7Throwing Distance, Relative Speed, and Severity of Injury 8Severity of Secondary Collision 14Conclusions 15References 16

C H A P T E R 2

Driver-Control Interaction of a Curve-Safe Braking Control for Motorcycles 19

Introduction 19Simulator 20

Vehicle Model 20Steering Model 21Brake-Control Strategy 23

Analysis 28Tractability 30Stability 30

Conclusion 31References 31

vi Contents

C H A P T E R 3

Motorcycle Rider Trajectory in Pitch-Over Brake Applications and Impacts 33

Introduction 34Crash Test 36

Test Design 36Results 37Video Analysis 39

Sled Tests 40Test Fixture Design 40Braking Simulation Development 42Results 43Video Analysis 45

Analysis 46Conclusions 51Acknowledgments 52References 52

C H A P T E R 4

Occupant Trajectory Model using Case-Specific Accident Reconstruction Data for Vehicle Position, Roll, and Yaw 55


Vehicle Model 57

Reference Frames 57

Initial Conditions 58

Equations of Motion 59

Occupant Model 59

Occupant in Vehicle 60

Occupant in Air 61

Occupant on Ground 63


vii

C H A P T E R 5

Motorcycle Tire/Road Friction 73Introduction 74Review of Previous Investigations 74Test Procedure 75Results 77Effects of Severe Wear 81Conclusions and Discussion 82References 83Acknowledgments 84Appendix 85

Data From Dry-Urface Tests 85Data From Wet-Surface Tests 89

C H A P T E R 6

Full-Scale Moving-Motorcycle-into- Moving-Car Crash Testing for Use in Safety Design and Accident Reconstruction 95

Introduction 96Crash Test Methodology 99

Test Facility 99Motorcycle Dolly 100Speed Control 102Impact Control 103

Test Design 104Test 1 104Test 2 105Test 3 106Test 4 107

Analysis 109Impact 109Deformation and Motion 109

Moving Motorcycle into Stationary Car 109

Moving Motorcycle into Moving Car—Test 1 113




Summary 124

Contents vii

viii Contents

Conclusion 127References 127Acknowledgments 128

C H A P T E R 7

Simulating Moving Motorcycle to Moving Car Crashes 129

Introduction 130Simulation Software 131Crash Tests 131Crash Test Simulations 133

Test 1 Analysis 133

Vehicle Models 133

Environment 135

Test 1 Simulations 135

Test 1 Simulation Summary 138

Test 2 Analysis 139

Vehicle Models 139

Environment 139

Test 2 Simulation 139


Test 3 Analysis 142

Vehicle Models 142

Environment 143



Test 4 Analysis 149

Vehicle Models 149

Environment 149



Discussion & Conclusions 154References 155Acknowledgments 156Appendix 157

Vehicle Data 157

ix

C H A P T E R 8

Time and Distance Required for a Motorcycle to Turn Away from an Obstacle 159

Introduction 160Literature Review 160

Daily, Shigemura, and Daily 160Lofgren, Mitchell, and Bonnett 161Limpert 161Watanabe and Yoshida 161Schibalski, Seeman, Weber, and Wolfer 162Rauscher 163Gilsdorf 164Shuman, Husher, Varat, and Armstrong 164Kasanický, Kohút, and Priester 164Benedikt et al. 165Giovannini, Savino, and Peirini 165Wright and Baxter 165

Current Work: 2 m Lateral Excursion 167Riders and Motorcycles 167Test Area 168Test Methodology 168

Results 168


C H A P T E R 9

Validation of Equations for Motorcycle and Rider Lean on a Curve 173

Introduction 174Motorcycle Lean on a Curve 175Assumptions 177Physical Testing—April 28, 2014 178Physical Testing—July 7, 2014 179Analysis and Results 180Conclusions 183References 183Acknowledgments 184Appendix 185

Contents ix

x Contents

C H A P T E R 10

Accident Characteristics and Influence Parameters of Severe Motorcycle Accidents in Germany 187

Introduction and Objectives 188Legal Regulation of Motorcycles in Germany 190Accident Studies Based on GIDAS (German In-Depth Accident Study) 191Database 192Evaluation Structure of the Study 193Injury Severity 193Accident Situation and Causes of Injury by Types of Accidents 195Collision Partners of Heavy Motorcycles and Closing Speed 197Cubic Capacity of Motorcycles 198Rider Individual Parameters (Age, Body Weight, Body Height, BMI) 199Collision Type and Injury Severity 200Multivariate Analysis 202Conclusion and Discussion 203References 207Acknowledgments 208

C H A P T E R 1 1

The Effects of Power Interruption on Electronic Needle-Display Motorcycle Speedometers 209

Introduction 209Testing Details 211

Power Interruption Testing 211Speedometer Drop Testing 211

Test Results 2121999 Harley Davidson FXDX 2122013 Harley Davidson FLTRU 2122015 Honda GL1800 Gold Wing 2132015 BMW R1200GS 2142014 Triumph T100 Bonneville 2142012 Kawasaki ZX-14R Ninja 214

xi Contents xi

Discussion 215Conclusion 216References 217Appendix 218

Appendix A Motorcycle VIN and Photographs 218Appendix B Speedometers Used in Drop Testing 219Appendix C Speedometers Used in Drop Testing after Disassembly 220

C H A P T E R 1 2

Testing Methodology to Evaluate Reliability of a “Frozen” Speedometer Reading in Motorcycle/Scooter Impacts with Preimpact Braking 221

Introduction 222History of Speedometer Technology 222Literature Review 224

Traffic Accident Investigation Manual, JS Baker, 1975 224Speedometer Examination: An Aid in Accident Investigation, FBI Law Enforcement Bulletin, 65920, 1980 224Post-Collision Speedometer Readings and Vehicle Impact Speeds, Collision Magazine, 2010 224Reliable Determination of Impact Velocity on the Basis of Indications of the Speedometer Stopped After the Collision, International Scientific Conference, 2009 225A Review of Speedometers and the Criteria to be Considered Before Accepting ‘Frozen’ Readings and Other Marks, EVU 2013-27, 2011 225An Assessment of Speedometers Using Stepper Motors to Hold Their Position during High Speed Impact Testing, ITAI Conference Proceedings, 2014 225The Behaviour of Instrument Clusters during High-Speed Crash Testing, EVU 2015 226

Accuracy of Retained Speedometer Readings, ITAI Conference Proceedings, 2014 226

Testing Process for Evaluating the Reliability of a “Frozen” Motorcycle Speedometer Needle Reading 226

Step 1—Identification of Gauge Needle Motor Type 227Step 2—Evaluation of Speedometer Needle Resistance 228Step 3—Gauge Needle Latency 229

Confirmed Stepper Motor Results 2301. 2008 Harley Davidson Heritage Softail Classic FLSTCI 2312. 2014 Harley Davidson Heritage Softail FLSTC103 2323. 2015 Harley Davison Street Glide Special FLHXS 232

xii Contents

4. 2014 Triumph Bonneville 2325. 2015 BMW R1200RT 2326. 2015 Indian Chieftain 2337. 2014 Triumph Tiger Explorer 233

Needle Movement at Power Loss 233Indeterminate Stepper Motor Results 234

8. 2006 Kawasaki Vulcan 900 Classic LT 2349. 2007 Kawasaki Ninja EX250 23410. 2012 Kawasaki Ninja EX250 23511. 2009 Honda Silver Wing FSC600 (Scooter 23512. 2015 Honda Gold Wing 1800 235

Antilock Braking Systems (ABS) and Traction Control 235Conclusions and Recommendations 236References 236Acknowledgments 237Appendix 238

Appendix A: 2008 Harley Davidson Softail Classic FLSTCI 238Appendix B: 2014 Harley Davidson Heritage Softail FLSTC103 239Appendix C: 2015 Harley Davidson Street Glide Special FLHXS 240Appendix D: 2014 Triumph Bonneville 241Appendix E: BMW R1200RT 242Appendix F: Indian Chieftain 243

C H A P T E R 1 3

Video Analysis of Motorcycle and Rider Dynamics During High-Side Falls 245

Introduction 246Site Inspection 246Case #1 248Case #2 251Case #3 254Case #4 255Speed Analysis from Audio Data 256Discussion and Conclusions 257References 260Acknowledgments 260



Volume 5: Heavy Vehicle Accident Reconstruction



contents

Introduction xiii

C H A P T E R 1

Heavy Truck Deceleration Rates as a Function of Brake Adjustment 1

Past Methods for Determining Deceleration Rates 2Regression Equations 3

Developed by the Vehicle Research and Test Center 3

Torque Factors for Differing Slack Adjusters Lengths 4

Modified Brake Sizing Equation 4Chamber Sizes not Covered in Regression Analysis 4

Braking Force for Wedge Brakes 7

Temperature Considerations 8Heat Effects on Pushrod Stroke 8

Determining Brake Temperatures 10

Validation Tests 11Texas A & M Tests 11

NHTSA Data 13

Summary of Calculation Method 131. Determine the Truck Tire/Road Coefficient of Friction 13

2. Obtain the Weight at Each of the Wheel Ends 13

3. Multiply the Truck Tire/Road Sliding Coefficient of Friction Times the Static Weight on Each Wheel to Obtain the Available Braking Force 14

4. Determine Air Chamber Size, Slack Adjuster Length, Drum Diameter, and Rolling Radius 14

5. Measure the Pushrod Stroke at 90 psi 14

6. Convert the Measured Pushrod Stroke to a Dynamic Stroke 14

7. Adjust the Dynamic Stroke for Heat Expansion if the Temperature of the Brakes is Known 14

8. Calculate the Attempted Braking Force for the Appropriate Chamber Sizes Using the Modified Brake Sizing Equation 15

vi Contents

9. Compare the Available Brake Force to the Attempted Brake Force at Each Wheel and Sum the Smaller Value From Each Wheel 15

10. Determine the Deceleration Rate for the Vehicle by Dividing the Total Braking Force by the Vehicle Weight 15

Summary and Conclusions 15References 16Appendix 17

C H A P T E R 2

Calculation of Heavy Truck Deceleration Based on Air Pressure Rise Time and Brake Adjustment 21

Introduction 21The Calculations 22

Step 1: Pushrod Force as a Function of Pressure 22

Step 2: Deceleration as a Function of Pressure 23

Step 3: Air Pressure as a Function of Time 23

Step 4: Deceleration and Speed Change as a Function of Time 26


C H A P T E R 3

Acceleration Performances Testing and Simulation of Various Types of Commercial Vehicles for Railway Crossing Design 29

Introduction 30Definition of Grade Crossing Sight Triangles 30Test Vehicles 31Acceleration Testing Procedure 31Results 32Acceleration Mathematical Model 34Charts for Departure Time Calculations 36Conclusions 38References 39

Contents vii

C H A P T E R 4

Calculation of Deceleration Rates for S-Cam Air-Braked Heavy Trucks Equipped with Antilock Brake Systems 41

Introduction 41Previous ABS-Analysis Techniques 42Air System Features 43Air Brake Chamber Characterization 44Calculating Lock Pressure 47Uncertainties 47Example 48Conclusion 49Acknowledgments 49References 49

C H A P T E R 5

Heavy Fire Apparatus Acceleration and Braking Performance 51

Introduction 52Fire Apparatus Standards 52

Auxiliary Stopping Devices 53

Test Methodology 54

Calculated Values 57

Previous Comparable Test Data 58

Braking Performance 58

Acceleration Performance 60

Test Results 60

Acceleration Performance From A Stop 60

Acceleration Performance From A Velocity 61

Braking Performance 61

Test Anomalies 63Summary/Conclusions 63References 64Acknowledgments 64Definitions/Abbreviations 65

viii Contents

Appendix 66Appendix A Test Run List 66

Appendix B Test Vehicle Specifications 69

Appendix C Acceleration Times by Position (Stopwatch) 78

Appendix D Calculated Acceleration Rate and Velocity by Position (meters per second)—Stopwatch 79

Appendix E Calculated Acceleration Rate Data—Average and Range 81

Appendix F VBOX III Average Acceleration Rate Data at Position by Classification—Vehicles 10-14 81

Appendix G VBOX III Acceleration Rate and Time Data By Position—Vehicles 10-14 82

Appendix H Pumpers over 15,875 kg (35,000 lbs) Maximum Braking—Calculated from Visual Observation 83

Appendix I Pumpers and Rescues under 15,875 kg (35,000 lbs) Maximum Braking—Calculated from Visual Observation 84

Appendix J Aerials—Maximum Braking—Calculated from Visual Observation 85

Appendix K VBOX III Acceleration Results Compared to Calculated Rates 85

Appendix L Maximum Acceleration Values Between Positions 1 and 3 86

Appendix M Maximum Braking Comparision between VBOX Data and Calculated Values—Service Brakes 87

Appendix N Maximum Braking Comparision between VBOX Data and Calculated Values—Service Brakes and Auxiliary Braking 87

Appendix O Moderate Braking Values—Service Brakes 87

Appendix P Vericom Braking Data for Pumpers over 15,875 kg 88

Appendix Q Vericom Braking Data for Pumpers under 15,875 Kg 88

Appendix R Vericom Braking Data for Aerials 89

C H A P T E R 6

Acceleration and Braking Performance of School Buses 91

Introduction 91Methodology 92Results 94

Acceleration 94

Bus 1 Acceleration Characteristics 94




Contents ix

Braking 113

Bus 1 Braking Characteristics 113




Summary/Conclusions 123Acceleration 123

Braking 124

References 124Acknowledgments 125

C H A P T E R 7

Low-Speed Acceleration of Tractor-Semitrailers Equipped with Automated Transmissions 127

Introduction 128Scope and Methodology 128Analysis and Results 130Uncertainty 132Conclusions 133References 134Acknowledgments 134Appendix A 135

C H A P T E R 8

Acceleration and Braking Performance of Transit-Style Buses 171

Introduction 172Bus Standards 172

Auxiliary Stopping Devices 173

Test Methodology 174Test Objectives 174

Weather 175

Instrumentation 175

Test Preparation 176

Acceleration Tests 176

Braking Tests 177

x Contents

Data Collected 178Idle Acceleration 178

Maximum Acceleration 180

Braking Tests 183

Additional Test Data 185

Straight Bus Acceleration 185

Articulated Bus Acceleration 185

Summary/Conclusions 186Test Anomalies 186

References 187Acknowledgments 187Definitions/Abbreviations 188Appendix 188

Appendix A: Test Bus Specifications 188

Appendix B: Straight Bus—Idle Acceleration Inflection Point Graph 190

Appendix C: Straight Bus—Maximum Acceleration Inflection Point Graph 191

C H A P T E R 9

Medium-Duty North American Delivery Van Frontal Barrier Crash Test Data for Crash Reconstruction 193

Introduction 194Test Methodology 194Test Site 194Test Vehicles 194

Test Vehicle 1: 1990 GMC 4500 Delivery Van 195

Test Vehicle 2: 1995 Oshkosh MT 195

Vehicle Instrumentation 196

Site/Barrier Instrumentation 197

Occupant Instrumentation and Performance Data 197

Test Results and Discussion 198Vehicle Dynamics 198

Test 1 (P33042-01) 198

Test 2 (P33042-02) 202

Summary/Conclusions 205References 206Acknowledgments 207

Contents xi

Appendix 208Appendix A—Pre- and Posttest Images of GMC Test Vehicle 208

Appendix B—Pre- and Posttest Images of Oshkosh Test Vehicle 210

Appendix C—Acceleration and Velocity Traces from the CG-X Accelerometer Data 212

C H A P T E R 1 0

Acceleration Testing of 2016 Kenworth T680 with Automated Manual Transmission in Auto Mode 215

Introduction 215Testing Methodology 216Results and Analysis 217Discussion 247References 248Acknowledgments 248

C H A P T E R 1 1

A Study of In-Service Truck Weights 249Introduction 250Literature Review 250Ontario Commercial Vehicle Survey 252Methodology 254Results 255Conclusions 258References 259Acknowledgments 259Definitions/Abbreviations 260Appendix 261

Appendix A: In-Service Truck Weight Data 261

Appendix B: Empty Truck Weight Data 298

Appendix C: Comparison between Studies 338

Appendix D: Schedules of Designated Vehicles and Combinations in Ontario 340

xii Contents

C H A P T E R 1 2

Acceleration Testing of 2016 Freightliner Cascadia with Automated Manual Transmission in Auto Mode 351

Introduction 351Testing Methodology 352Results and Analysis 354Discussion 384References 385Acknowledgments 385



Volume 6A: Rollover Accident Reconstruction



contents

Introduction xxix


The Dynamics of Previously Conducted Full-Scale Heavy Vehicle Rollover Crashes 1

Introduction 1Approach 2

Cases Studied 2

Roll Rate at Impact 2

Vertical Speed at Impact 3

Results 4Comparison with Simulation Results 5Conclusion 8Acknowledgments 8References 9


Tractor-Trailer Rollover Crash Test 11Introduction 12Event Selection 13Rolltek System 14Roll Sensor 14The Suspension Seat Safety System (S4) 15Seat-Mounted Rollover Airbag (SRA) 16Simulation 16Rollover Test Setup 17Test Results 18Conclusions 22References 22

vi Contents


Rollover Dynamics: An Exploration of the Fundamentals 25


Test Setup 27

Posttest Documentation 28

Test Analysis 28

Reconstruction Analysis 29

Results 30Measured Results 30

Reconstructed Results 42

Discussion 47Recommendations 52

Conclusions 54References 54Acknowledgments 56Definitions, Acronyms, Abbreviations 56Appendix A Test Surface Mappings for Tests 1 and 2 57Appendix B Vehicle Position Layouts for Tests 1 and 2 59


Analysis of a Real-World High-Speed Rollover Crash from a Video Record and Physical Evidence 61

Introduction 62Subject Incident 62

Video Record of Incident 63

Objectives 64Background 64

Roll Mechanics Technical Approach 64

Physical Evidence 65Subject Vehicle Inspection 66

Crash Site Inspection 68

Correlation and Analysis of Video Record and Physical Evidence 70

Determination of Seven Key Video Frames 71

Key Frame 1 71

Key Frame 2 72

Key Frame 3 72

Key Frame 4 72

Contents vii

Key Frame 5 72

Key Frame 6 72

Key Frame 7 73

Key Position 8 73

Video Record Quantitative Analysis 73

Reliability of Frame Rate as an Event Timer 75

Vehicle Speed Analysis 76

Vehicle Drag Factor 77

Uncertainty Analysis 77

Crash Sequence Analysis 79Yaw Sequence 80

Rollover Sequence 81

Rollover Mechanics 82Drag Factor 82

Rollover Angle 84

Rollover Rate 85

Centripetal Acceleration and Tangential Velocity 87

Energy Dissipation 88

Comparison with Reconstructed Values 89

Conclusions 91Acknowledgments 91References 91Appendix A. Accident Sequence Photographs Obtained from Video Record 93Appendix B. Three-Dimensional Rendered View of Roll Sequence from Figure 11 94Appendix C. Magnified Top View of Rollover Sequence from Figure 11 95


Development of a Variable Deceleration Rate Approach to Rollover Crash Reconstruction 97

Introduction 98Preview of Conclusions 100Analyzing Vehicle-to-Ground Impacts 102Roll Velocity History Characteristics 109Deceleration During a Ground Impact 114Comparison with Crash Test Data 117Discussion 122References 123Appendix A – Derivation of Critical Impulse Ratio Equation 125Appendix B - Calculating an Average Deceleration Rate 126

viii Contents


Measurement and Modeling of Rollover Airborne Trajectories 129

Introduction 130Objectives 131Technical Approach 131

Rollover Trajectory Mechanics Theory 131

Method for Trajectory Theory Evaluation 134

Rollover Crashes Utilized in Study 134Dolly Rollover Test 134

Real-World Rollover 135

Results of Dolly Test and Real-World Rollover 135Vehicle Elevation Change During Rollover 136

Rollover Trajectory Results and Discussion 137Effectively Airborne Evaluation 138

Trajectory Model Application 139

Uncertainty Analysis in Model Application 142

Conclusions 143Acknowledgments 143References 144Nomenclature 144

Subscripts 145

Appendix A Derivation of Equation (5) 145Appendix B Example Digital Vehicle Model Overlay From Dolly Rollover 146Appendix C Video Frame Depiction of High-Speed Dolly Rollover Test 147Appendix D Roll Mechanics Results for High-Speed Dolly Rollover 148Appendix E Frame Captures for Study Portion of Real-World Crash 149


Analysis of a Dolly Rollover with PC-Crash 151Introduction 152The Dolly Rollover Crash Test 154PC-CRASH Input Parameters 155Results 159Discussion and Conclusions 162References 166

Contents ix


ATV Rollover Resistance: Testing of Side-By-Side ATV Rollover Initiations 169

Introduction 170Experimental Methods 170

Test Vehicle: Static Calculations 170

Test Vehicle: Measuring Moments of Inertia 171

Test Results: SSF and Inertias 172

Test Procedure: Dynamic Testing 173

Slowly Increasing Speed Maneuver 173

Testing Results 173

Discussion 175

Tire Properties of RUVs 175

Important Considerations Related to RUV Roll Initiation 175



Rollover Testing of Recreational Off-Highway Vehicles (ROVs) for Accident Reconstruction 179


Test Vehicle Preparation 180

Test Procedure 181

Results 182Scratch Mark Analysis 183



Computer Simulation of Steer-Induced Rollover Events via SIMON 209

Introduction 210Vehicle Dynamics Model 211

x Contents

Full-Scale Rollover Tests 211Test A: 1985 Toyota Pickup 212

Test B: 1991 Ford Explorer 215

Test C: 1997 Toyota 4Runner 219

Test D: 1989 Ford Aerostar 224

Summary/Conclusions 230References 234Acknowledgments 236Appendix A Simulation Vehicle Data for Toyota Pickup 237Appendix B Simulated Vehicle Data for Ford Explorer 242Appendix C Simulated Vehicle Data for Toyota 4Runner 247Appendix D Simulated Vehicle Data for Ford Aerostar 252


Comparison of Linear Variable Deceleration Rate Rollover Reconstruction to Steer-Induced Rollover Tests 257

Introduction 258Method 259Results 260Discussion 260Conclusion 264References 264Definitions 264Appendix 265

Appendix A 265


An Integrated Model of Rolling and Sliding in Rollover Crashes 271

Introduction 272Theory 273Methods 278Results 279Discussion 282Conclusions 285

Contents xi



On the Directionality of Rollover Damage and Abrasions 293

Introduction 294Methods 295Results 296Discussion 307

Scratch Orientation Groups 307

Scratch Direction 310

Scratch Orientation and Direction in the Field 312

Conclusions 313References 313


Glass Debris Field Longevity for Rollover Accident Reconstruction 315

Introduction 316Use of Glass Debris Field in Reconstructing Rollover Crashes 316Methods 316Results 317Discussion 320Conclusions 323References 323



Volume 6B: Rollover Accident Reconstruction



contents

Introduction xxix


Vehicle Linear and Rotational Acceleration, Velocity, and Displacement during Staged Rollover Collisions 1


Vehicles 2

Sled 2

Instrumentation 2

Video 3

Test Procedure 3Results 4

Accelerometer Data Processing 5

Discussion 9Conclusions 13Acknowledgments 14References 14Appendix A 15

Instrumentation 15

Appendix B 17Buick Photographs 17

Oldsmobile Photographs 18

Pontiac Photographs 19

Mercury Photographs 20

Appendix C 21Buick Accelerometer Data 21

Oldsmobile Accelerometer Data 23

Pontiac Accelerometer Data 25

vi Contents


Rollover Crash Tests on Dirt: An Examination of Rollover Dynamics 27

Introduction 28Methods 28Results 31Discussion 39Conclusions 41Acknowledgments 41References 41


A Method for Determining the Vehicle-to-Ground Contact Load during Laboratory-Based Rollover Tests 43

Introduction 44Background 44

(1) Method for Measurement of Dynamic Structural Deformation 45

(2) Means to Monitor Vehicle-to-Ground Contact Load 46

Methodology 47Generation of a FEA Model of the Test Vehicle 47

Validation of the FEA Model 47

Camera-Matching Video Analysis of Image 48

Simulation Procedure 48

Results 49Conclusions 52Acknowledgments 53References 53


Vehicle and Occupant Responses in a Friction Trip Rollover Test 55


Analysis of Impact Biomechanics 59

Simulation of Vehicle and Occupant Kinematics Vehicle Motion Model 59

Occupant and Restraint Kinematics Model 60

Contents vii

Results 60Vehicle and Dummy Responses 60

Responses at Peak Neck Compression 68

Analysis of the Z-Axis Dynamics 73


Discussion 79Effect of a Rigid Roof 79

Improving Occupant Safety in a Rollover 80

Dynamic Stiffness of the Hybrid III Neck 82

Injury Mechanism 82

References 83


Rollover Testing on an Actual Highway 87Introduction 88

Loss of Control 88

Tripping 88

Rollover 88

Objective 89Methods 89

Rural Highway Testing 89

General Test Procedure 89

General Test Documentation 91

Closed Test-Track 92

Test Procedure 92

Test Documentation 93

Results 93Loss-of-Control Phase 94

Tripping Phase 95

Trip Velocity Extrapolation 96

Trip Velocity Integration 96

Rolling Phase 97

Discussion 101Conclusions 102Acknowledgments 104References and Biblography 104Appendix Test #1 1996 Buick Skylark No-Roll 106Appendix Test #2 1996 Buick Skylark 6 Rolls 109Appendix Test #3 1984 AMC Eagle 3 Rolls 112Appendix Test #4 1987 Ford Taurus No-Roll 115

viii Contents

Appendix Test #5 1987 Ford Taurus 1 Roll 118Appendix Test #6 1991 Ford Escort 8 Rolls 121


Review and Comparison of Published Rollover Test Results 125

Introduction 126History and Description of RTD 126

The NHTSA RTD History 127

The NHTSA RTD Test Configuration 128

Methodology 129Review and Analysis of NHTSA RTD Test Data 130

Calculation Method for Determining Vehicle Average Deceleration 131

Results 132Results of NHTSA RTD Rollover Crash Test Analysis 132

Analysis of Rollover Data Other than NHTSA RTD Rollover Test Data 134

Comparison of NHTSA RTD Rollover Test Data with Other Rollover Data 135

Summary/Conclusions 138References 139Additional Sources 140Acknowledgments 140Appendix 141

Appendix A Summary of Nhtsa Rollover Tests 141

Appendix B Summary of Rollover Test Analysis 142

Appendix C Graphs 146


Dynamic Response of Vehicle Roof Structure and ATD Neck Loading During Dolly Rollover Tests 151

Introduction 152Forester Rollover Test Series: Overview 154Forester Test Series: Vehicle Setup 154Forester Test # 1: Dirt Surface 158Forester Test # 2: Concrete Surface 166Forester Test # 3: Dirt Surface 170Kinematics and Energy Analysis 183

Contents ix

Conclusions 188References 189Acknowledgments 190Appendix A 191

Forester Rollover Research Test Series Summary 191

Forester Test #1 on Dirt 191

Forester Test #2 on Concrete 195

Forester Test #3 on Dirt With ATDS 195

Appendix B 202Glass Fracture Analysis 202


Rollover Testing of Sport Utility Vehicles (SUVs) on an Actual Highway 205

Introduction 206Objective 206Method 207



Onboard Instrumentation 210

Photographs and Video 211

Measurements of Physical Evidence 211

Results 212Loss-of-Control Phase 212

Tripping Phase 213

Rolling Phase 215

Discussion 217Loss-of-Control Discussion 220

Tripping Phase Discussion 221

Rolling Phase Discussion 221

Conclusions 222References 223Acknowledgments 224Appendix 225

Notes 225

1996 Oldsmobile Bravada 10.5 Rolls Test #1 2271991 Isuzu Rodeo 7.0 Rolls Test #2 2301994 Nissan Pathfinder No Roll Test #3 2331994 Nissan Pathfinder 3.5 Rolls Test #4 2362002 Ford Explorer No Roll Test #5 2392002 Ford Explorer 2.0 Rolls Test #6 242

x Contents

1998 Ford Expedition 1.5 Rolls Test #7 2451991 Mitsubishi Montero 8.5 Rolls Test #8 248


ATV Rollover Resistance: Testing of Side-By-Side ATV Rollover Initiations 251


Test Vehicle: Static Calculations 252

Test Vehicle: Measuring Moments of Inertia 253

Test Results: SSF and Inertias 254

Test Procedure: Dynamic Testing 255

Slowly Increasing Speed Maneuver 255

Testing Results 255

Discussion 257

Tire Properties of RUVs 257

Important Considerations Related to RUV Roll Initiation 257



Evaluation of Dynamic Roof Deformation in Rollover Crash Tests 261

Introduction 262Test Series Description 263

Vehicle Instrumentation 265

High-Speed Digital Motion Cameras 265

Data Analysis 267Analysis of String Potentiometer Motion 267

Determining Dynamic Roof Deformation by Trilateration 267

Closed-Form Solution 271

Numerical Methods 271

Onboard 3D Photogrammetry 274

String Potentiometer vs. 3D Photogrammetry Data 275

Error Sources in Measurement 280

String Potentiometers 280

3D Photogrammetry 280

Post-Test Coordinate Measurements vs. End-of-Test Coordinate Locations 281

Measurement Technique Limitations 285

Contents xi


Test Data 289


Comparing Dolly Rollover Testing to Steer-Induced Rollover Events for an Enhanced Understanding of Off-Road Rollover Dynamics 305

Introduction 306Methods 307Results 309

Peer Rollover Events 314

Group A 315

Group B 318

Discussion 319Conclusions 322References 323Appendix 325


Rollover Crash Test Results: Steer-Induced Rollovers 333

Introduction 334Prior Publication of Steer-Induced Rollover Tests 334

Rollover Phases 334

Roll Phase 335

Rollover Drag Factor 335

GPS Speed Sensor 336

Methodology 336Test Setup 336

Vehicle Preparation 337

Crash Site Documentation 339

Test Vehicle Documentation 339

Rollover Reconstruction 339

Rollover Phase Duration 339

Over-The-Ground Speed Calculation 340

xii Contents

Verification of GPS Sensor Speed Output 341

Data Filtering 342

Results 342Rollover Tests 342

GPS Speed Output Verification Test 346

Trip Point 346

Discussion 348GPS Sensor Output Correction 348

Average Drag Factors 351

Bilinear Decelerations and Roll Rate Peak 351

Trip Point 352

Observations 352Conclusions 353Acknowledgments 353References 353Appendix A 355

Test Data 355


Rollover Testing of Recreational Off-Highway Vehicles (ROVs) for Accident Reconstruction 371


Test Vehicle Preparation 372

Test Procedure 373

Results 374Scratch Mark Analysis 375



Rollover Initiation Simulations for Designing Rollover Initiation Test System (RITS) 401


Vehicle Modeling 403

Vehicle Validation 404

Contents xiii

Static Tests 404

Dynamic Rollover Tests 404

Effect of Initial Speed 404

Monte Carlo Analysis 405

RITS Overview 405

RITS Simulation Set-Up 406

Deceleration Pulse 406

Required Acceleration 407

Sensitivity Analysis 407

Results 407Model Validation 407

Effect of Initial Speed on Vehicle Kinematics 409


Touchdown Conditions vs. Required Acceleration 411

Change of the Speed of the Sled and Tripping Time 411

Touchdown Conditions vs. Deceleration Pulse 411

Discussion 413Vehicle Model 413

Effect of Initial Speed on Vehicle Kinematics 413


Ranges of Touchdown Parameters 413

Touchdown Parameters vs. Required Acceleration 413

Touchdown Parameters vs. Deceleration Pulse 414


Vehicle Testing 416

Model Validation 416

K&C validation 416

Dynamic Rollover Test Validation 418


Rollover Testing of a Sport Utility Vehicle (SUV) with an Inertial Measurement Unit (IMU) 423




Onboard Instrumentation 428

Video and Photographs 429

Measurements of Physical Evidence 429

xiv Contents

Results 430Pre-trip Phase 431

Tripping Phase 432

Rolling Phase 432

Data Correlation 433

Discussion of Results 434Positional Data 434

Velocity Data 435

Acceleration Data 438

Angular Velocity Data 440

Reconstruction Data 440

Conclusions 444Methodology 444

Documentation 444

Instrumentation 444

Rollover 445




Volume 6C: Rollover Accident Reconstruction


©2019 SAE International v

contents

Introduction xxix

V O L U M E 6 C — C H A P T E R 1

Methodology for Simulation of Rollover Cases 1Introduction 1

Short History in Rollover Research 1

Short History in Rollover Tests 2

Short History in Rollover Protection 3

The Necessity for Rollover Methodology 3

Rollover Tool Chain Methodology 4Application and Results of the Rollover Tool Chain 5

Accident Scenario Module (ASM) 6

Active Safety Systems Design Module (ASSDM) 7

Restraint Systems and Interior Design Module (RSIDM) 9

Benefit and Injury Assessment Module (BIAM) 11

Conventional Assessment Parameters 11

Injury Assessment Parameters 12

Harm Assessment Parameters 13

Conclusion 14Acknowledgments 14References 14Definitions, Acronyms, Abbreviations 16


Dolly Rollover Testing of Child Safety Seats 17Introduction 18Methodology 19Results 21

vi Contents



Trajectory Model of Occupants Ejected in Rollover Crashes 27


Generalized Vehicle Dynamics Model 29

Occupant Ejection Model 30

Model Parameter Optimization 32

Model Validation 33

Results 34Dolly Rollover Test 34


Model Validation 36

Discussion 38Conclusions 40Acknowledgments 41References 41


Modelling the Effects of Seat Belts on Occupant Kinematics and Injury Risk in the Rollover of a Sport Utility Vehicle (SUV) 43

Introduction 44Reconstruction and Validation of a Rollover Test 45

Rollover Test Descriptions 45

Reconstruction of the Rollover Test 45

Injury Evaluation 46

Validation of the Reconstruction 47

Results of Simulations 48Dummy Simulation with Seat Belts 48

Dummy Kinematics 48

Injury Analysis 48

Contents vii

Dummy Simulation Without Seat Belts 48

Dummy Kinematics 48

Injury Analysis 49

Human Body Simulation with Seat Belts 49

Human Body Kinematics 49

Injury Analysis 49

Human Body Simulation Without Seat Belts 50

Human Body Kinematics 50

Injury Analysis 50

Comparison 50

Discussion 52Human Body Model 52

Muscular Activation 52

Seat Belts 52

Roof Intrusion 53

Vehicle Movement 53

Injury Evaluation 53

Conclusions 53Acknowledgments 54References 55Appendix 58


Soil-Trip Rollover Simulation and Occupant Kinematics in Real-World Accidents 65

Introduction 66Soil-Trip-Over 67

Rollover Accident Reconstruction with PC-Crash 67

Simplified Car Model for Soil-Trip-Over Simulation 69

Selection of Parameters of Simplified Soil-Trip Rollover Simulation 69

Results of Simplified Soil-Trip Rollover Simulation 70

Full Car Soil-Trip Rollover Simulation 70

Full Car Soil-Trip Rollover Simulation Results 71

Comparison of Kinematics in Dummy and Human Model 72Conclusions 76References 76Acknowledgments 77

viii Contents


Occupant Ejection Trajectories in Rollover Crashes: Full-Scale Testing and Real-World Cases 79


Volvo XC90 Dolly Rollover Test 80

Real-World Rollover Crashes 81

Lincoln Navigator Rollover 81

GMC Yukon Denali Rollover 82


Results 83Volvo XC90 Dolly Rollover Test 83

Real-World Cases 84

Lincoln Navigator Rollover 84

GMC Yukon Denali Rollover 85

Comparison to Dolly Rollover Tests 88

Ejection Marks 90

Discussion 90Conclusions 93Acknowledgments 93References 93


Occupant Trajectory Model Using Case-Specific Accident Reconstruction Data for Vehicle Position, Roll, and Yaw 95


Vehicle Model 97

Reference Frames 97

Initial Conditions 98

Equations of Motion 99

Occupant Model 99

Occupant in Vehicle 100

Occupant in Air 101

Occupant on Ground 103

Contents ix



Vehicle and Occupant Responses in a Friction Trip Rollover Test 113


Analysis of Impact Biomechanics 117


Occupant and Restraint Kinematics Model 118

Results 118Vehicle and Dummy Responses 118

Responses at Peak Neck Compression 126

Analysis of the Z-Axis Dynamics 131


Discussion 137Effect of a Rigid Roof 137

Improving Occupant Safety in a Rollover 138

Dynamic Stiffness of the Hybrid III Neck 140

Injury Mechanism 140

References 141


Dynamic Response of Vehicle Roof Structure and ATD Neck Loading During Dolly Rollover Tests 145

Introduction 146Forester Rollover Test Series: Overview 148Forester Test Series: Vehicle Setup 148Forester Test # 1: Dirt Surface 152Forester Test # 2: Concrete Surface 160Forester Test # 3: Dirt Surface 164

x Contents

Kinematics and Energy Analysis 177Conclusions 182References 183Acknowledgments 184Appendix A 185

Forester Rollover Research Test Series Summary 185

Forester Test #1 on Dirt 185

Forester Test #2 on Concrete 189

Forester Test #3 on Dirt With ATDS 189

Appendix B 196Glass Fracture Analysis 196


Validation of Occupant Trajectory Model Using the Ford Expedition Dolly Rollover Experimental Test Data 199


Reference Frames 201

Vehicle Evolution 202

Occupant at Ejection 202

Occupant at POR 205

Results 205Discussion 208Conclusion 212References 212Appendix 214

Appendix A 214



Volume 7A: Event Data Recorder Interpretation



contents

Introduction xxv


The Efficacy of Event Data Recorders in Pedestrian-Related Accidents 1


Test Vehicles 2

Pedestrian Dummy 2

Test Procedure 3

Data Acquisition and Post Processing 3

Results 3Discussion 6Conclusion 9Acknowledgments 9References 9


Accuracy of Powertrain Control Module (PCM) Event Data Recorders 11


Results 14

Discussion 21VBOX Data Synch 21

Induced Errors 21

Conclusions 22Acknowledgments 22References 23Definitions, Acronyms, Abbreviations 23Appendix 1: Apparatus 24

vi Contents


Accuracy of Selected 2008 Chrysler Airbag Control Module Event Data Recorders 27

Introduction 27Results 29

2008 Jeep Commander ACM EDR Vehicle Speed vs. Racelogic VBOX III at 100 Hz 29

2008 Commander Brake Switch Reporting Latency 32

2008 Dakota ACM EDR Vehicle Speed vs. Racelogic VBOX III 32

Dakota Brake Latency 36

Acceleretor Pedal Accuracy 36

Foot Movement Time from Accel to Brake 38


Data Truncation 39

Statistical Analysis 39

Conclusions 39Commander Speed Accuracy 39

Dakota Speed Accuracy 39

Brake Switch Latency 40

Accelerator Pedal Position Accuracy 40

Reporting Frequency 40

Acknowledgments 41References 41Definitions, Acronyms, Abbreviations 41Appendix: Apparatus 42


Accuracy of Selected 2008 Ford Restraint Control Module Event Data Recorders 45

Introduction 45Sources of Vehicle Speed in EDRs 46

2008 Ford Focus and Edge Restraint Control Module 46

Results 472008 Ford Focus RCM vs. Racelogic VBOX II 47

2008 Edge RCM vs. Racelogic VBOX II 52

Focus/Edge Brake Switch Latency 56

Focus/Edge Accelerator Pedal Data Accuracy 57


Contents vii

EDR Speed Data Precision 58

EDR vs. Can Bus Speed Data Accuracy 58

Conclusions 592008 Ford Focus/Edge EDR Speed vs. VBOX 59

2008 Focus/Edge Brake Switch Latency 59

2008 Focus/Edge Accelerator Pedal Percent Accuracy 59

Acknowledgments 59

References 60Definitions, Acronyms, Abbreviations 60Appendix 61


Accuracy of EDR During Rotation on Low-Friction Surfaces 65

Introduction 66Prior Art 66

Test Procedure 66

Results 68

Braking Mode Results 68

Heavy Throttle/Acceleration Test Runs 72

Light to No Accelerator Pedal Applied Results 74

Summary/Conclusions 76Braking Runs 76

Acceleration Runs 76

Light/No Throttle Runs 77

Overall 77

Future Research 77



Chrysler Airbag Control Module (ACM) Data Reliability 99


Test Runs 101

Results 103

Summary/Conclusions 119

viii Contents



Accuracy of Event Data Recorder in 2010 Ford Flex During Steady-State and Braking Conditions 135

Introduction 136Purpose 136


Test Procedure 138Description of the Test Vehicle 138

Synchronizing Data Sources 139

Data Analysis and Results 140EDR to GPS Speed Differences 140

Steady Driving 141

Aggressive Braking 141

Regression Analysis Results 143

EDR to can Speed Differences 143

Data Truncation 143

Data Timing 143

GPS Speed Data and CAN Speed Data 144

Dependence on Acceleration 144

Accuracy and Timing of Other EDR Parameters 146

Accelerator Pedal Data 146

Timing of Brake Indicator 146

Applications and Example 146Speed without Braking 146

Speed during Braking 147

Method 1: Data Driven Bounds 147

Method 2: Kinematic Relationship 147

Summary and Conclusions 148 Speed Data without Braking 148

Speed Data during Braking 148

Remarks 149


Contents ix


Evaluation of Camry HS-CAN Pre-crash Data 163Introduction 163HS-CAN Messages 164Vehicle Speed 164HS-CAN Speed Evaluation 165Speed Correlation Tests 166Speed Analysis 166Discussion 170Engine Speed 170Analysis 171Discussion 173Accelerator Pedal Position 173

HS-CAN Measurement of APPS #1 173

Analysis 174

Discussion 176

Brake 176Discussion 178

Event Data Recorder 178Analysis 178

Engine rpm 178

Vehicle Speed 180

Brake Status and APPS #1 180

Conclusions 180Vehicle Speed 180

Engine Speed 180

Accelerator Pedal Position Sensor 180

Brake Application 181

EDR Correlation 181


Test Vehicle and Instrumentation 182


Confirmation of Toyota EDR Pre-crash Data 185

Introduction 186EDR Location 187

x Contents

Recording EDR Events 187Data Tolerances 187Test Methods and Results 188

Setup and Test Matrix 188

Test Results and Analysis 189

Summary/Conclusions 190References 191Definitions/Abbreviations 191Appendix 192

Appendix A: Tolerance Factors 192

Appendix B: Test Conditions 192

Appendix C: Test Conditions 193

Appendix D: Camry Plots 194

Appendix E: 4Runner Plots 196

Appendix F: Prius Plots 198

V O L U M E 7 A — C H A P T E R 1 0

Accuracy of Event Data in the 2010 and 2011 Toyota Camry During Steady-State and Braking Conditions 201

Introduction 202Literature Review 202Theory of Operation 204Data Collection Procedure 205Data Analysis and Discussion 206

Can Bus Data 206

Steady-State Vehicle Speed 208

Speed During Heavy Braking 209

Factors Affecting Speed Difference 212

Speed Message Timing 213

Timing from Trigger to First Data Point 214

Other ACM-Recorded Precrash Values 217

Summary/Conclusions 218Limitations 219References 220Acknowledgments 221Definitions/Abbreviations 221Appendix 222

Contents xi


Assessing the Accuracy of Vehicle Event Data Based on CAN Messages 225

Introduction 226Related Previous Work 226

Networking Principles 226

Accuracy Analysis: Can Data Only 228Experiment Description 228

Data Recording: Preparation and Implementation 228

Data Analysis 228

Experimental Results 230

Accuracy Analysis: Can and EDR Data 232Experiment Description 232

Data Recording: Preparation and Implementation 233

Experimental Results 234

Speed Accuracy 235

Message Timing 235

Arduino Hardware Platform 237Hardware 237

Software 238

Arduino Future Development 239

Summary and Conclusions 239References 240Acknowledgments 241Appendix 242

Appendix A: Powerspec—Sudden Deceleration Data Report 242


Accuracy of Pre-crash Speed Recorded in 2009 Mitsubishi Lancer Event Data Recorders 245

Introduction 246Test Vehicle 248Data Collection Procedure 250

Test Series #1 251

Test Series #2 251

Synchronizing Data Sources 251

Results 252Test Series #1 252

Test Series #2 253

xii Contents

Discussion 255Conclusions 257References 258Acknowledgments 259Appendix A 259



Volume 7B: Event Data Recorder Interpretation



contents

Introduction xxv


Accuracy and Characteristics of 2012 Honda Event Data Recorders from Real-Time Replay of Controller Area Network (CAN) Traffic 1

Introduction 3Literature Review 3Methodology 6

Data Collection 6

Nondeployment Event Generation 9

CAN Replay Experiments 11

Results and Discussion 12CAN Identifier Maps 12

CAN Speed Accuracy Tests 15

2012 CR-V Normal Driving 15

Civic Steady State 16

CDR Reported Precrash and Crash Data 17

2012 CR-V Accuracy during Maximum ABS Braking 17

2012 Civic EDR Accuracy during Maximum ABS Braking 20

Timing between 0 and −0.5 Data Points in the Precrash Data 22

Dynamic Steering Maneuvers 23

Conclusions 25Data Accuracy Testing Methodology 25

2012 CR-V Speed Data 25

2012 Civic Speed Data 25

Other SRS Reported Data 26

Acknowledgments 26Nomenclature 26References 26

vi Contents

Appendix 28Appendix A: Honda Can Bus IDS 28

Appendix B: Can Replay System Design 29

Data Transformation and Storage 29

Design Considerations for CAN Transmission 29Windows PC 30

Real-Time Operation System 30

Field Programmable Gate Array 30

Replay Timing Feedback 30

Software Implementation 31

Appendix C: Time Adjustment for Civic Data 34


Validation of Event Data Recorders in High Severity Full-Frontal Crash Tests 37

Introduction 38Delta-V Accuracy 38

Speed Data Accuracy 39

Seatbelt Buckle Accuracy 39

Objective 39Approach 39

Development of the EDR Dataset 40

Crash Test Instrumentation Selection 40

Event Recording Complete Status 40

Seatbelt Buckle Status 41

Airbag Deployment 41

Precrash Vehicle Speed 41

Delta-V 41

Time Zero Alignment 41

Delta-V Alignment 44

Results 44Seatbelt Buckle Status 44


Pre-crash Vehicle Speed 45

Delta-V 46

Discussion 49Conclusions 50References 51Definitions/Abbreviations 52Appendix 53

Contents vii


The Accuracy and Sensitivity of 2005 to 2008 Toyota Corolla Event Data Recorders in Low-Speed Collisions 69


Instrumentation 71

Test Procedure 71

Vehicle Tests 71

Sled Tests 72

Data Reduction 72

Results 74Vehicle Tests 74

Frontal Impacts 74

Rear-End Impacts 75

Sled Tests 76

Vehicle Crash Pulse Replications 76

Haversine Crash Pulses 76

ACM Model 78

Repeatability 80

Trigger Event Overwriting Logic 80

Discussion 80Conclusions 82References 83Acknowledgments 83Appendix 84


Accuracy of Translations Obtained by 2013 GIT Tool on 2010-2012 Kia and Hyundai EDR Speed and Delta V Data in NCAP Tests 87

Introduction 87Literature Search 88

Kia and Hyundai Tool 89

Methods 90Results 92

Precrash Speed Data Time Series (Element 2-1) 92

Longitudinal Delta V Time Series (Element 1-1) 93

viii Contents

Maximum Longitudinal Delta V (Element 1-2) 93

Time to Maximum Delta V (Element 1-3) 94

Lateral Delta V Time Series (Element 1-4) 94

MDB Tests 94

Pole Tests 95

Maximum Lateral Delta V (Element 1-5) 96

Time to Max Lateral Delta V (Element 1-6) 97

Time to Max Total Delta V (Element 1-7) 97

Discussion 97Conclusions 97References 98Acknowledgments 99Definitions/Abbreviations 99Appendix 100

Appendix 1 - Frontal Crash Test Longitudinal Delta V in EDR versus Reference 100

Appendix 2 - Frontal Crash Test Speed Prior to Impact in EDR versus Reference 103

Appendix 3 - EDR Memory Section 1 Elements “Stoplight Chart” by Test Type (Green Indicates Plausible, Yellow not Expected, Red Implausible for the Test) 104

Appendix 4 - EDR Memory Section 2 Data Elements 1-16 by Test Type 105

Appendix 5 - EDR Section 2 Elements 17-34 Stoplight Chart 106

Appendix 6 - EDR Section 3 Data Elements And Current Data Stoplight Chart by Test Type 107

Appendix 7 108

Appendix 8 - Chart of Kia/Hyundai Models that were Tested in this Study versus Models Officially Supported by the EDR Tool 112

Appendix 9 - Discussion of Other Data Elements 113

Rollover (Element 1-8) 113

Throttle Time Series (Element 2-2) 113

Brake Time Series (Element 2-3) 113

Ignition Cycles at Event (Element 2-4) 113

Driver Belt Status (Element 2-5) 113

Airbag Warning Light On (Element 2-6) 113

Time to Deploy Frontal Driver Stage 1 (Element 2-7) 113

Time to Deploy Frontal Passenger Stage 1 (Element 2-8) 114

Event Number (Element 2-9) 114

Time Between Events (Element 2-10) 114

Event Recording Complete (Element 2-11) 114

RPM Time Series (Element 2-12) 114

ABS On/Off Time Series (Element 2-13) 114

Stability Control On/Off Time Series (Element 2-14) 114

Contents ix

Steering (Element 2-15) 115

Passenger Belt Status (Element 2-16) 115

Driver Seat Position Forward (Element 2-17) 115

Passenger Seat Position Forward (Element 2-18) 115

Driver Occupant Classification System (Element 2-19) 115

Passenger Occupant Classification System (Element 2-20) 115

Time to Deploy Driver Frontal Airbag St. 2 (Element 2-21) 115

Time to Deploy Pass Frontal Airbag St. 2 (Element 2-22) 116

Time to Deploy Driver Side Airbag (Element 2-23) 116

Time to Deploy Passenger Side Airbag (Element 2-24) 116

Time to Deploy Driver Side Curtain (Element 2-25) 116

Time to Deploy Passenger Side Curtain (Element 2-26) 116

Time to Deploy Driver Pretensioner (Element 2-27) 116

Time to Deploy Passenger Pretensioner (Element 2-28) 116

Driver 2nd Stage Airbag Disposal (Element 2-29) 116

Driver 3rd Stage Airbag Disposal (Element 2-30) 117

Passenger 2nd Stage Airbag Disposal (Element 2-31) 117

Passenger 3rd Stage Airbag Disposal (Element 2-32) 117

Time to Deploy Driver Stage 3 (Element 2-33) 117

Time to Deploy Passenger Stage 3 (Element 2-34) 117

Longitudinal Acceleration Time Series (Element 3-1) 117

Lateral Acceleration Time Series (Element 3-2) 117

Vertical Acceleration Time Series (Element 3-3) 117

Ignition Cycles at Download (Real Time Element) 117

Second Events 118

Hex Data 118


Validation of Event Data Recorders in Side-Impact Crash Tests 119

Introduction 120Objective 120Approach 120

Development of the EDR Dataset 121

Event Recording Complete Status 121

Crash Test Instrumentation Selection 121

Delta-V 122

Rotation Correction 123

Time Zero Alignment 124



x Contents

Results 127Delta-V 127



Discussion 130Conclusions 131References 132Acknowledgements 133Abbreviations 133Appendix 134


Accuracy and Timing of 2013 Ford Flex Event Data Recorders 161

Introduction 162Motivation 162

Objective 162


Overview and Organization 163

Procedure 163Driving Data Acquisition 163

CAN ID Reverse Engineering 164

Acceleration Sled Testing 164

Results 166Steady State Speed Testing 166

Speed Data During Hard Braking 169

Pre-crash Stability Control Data: Longitudinal Acceleration 172

Pre-crash Stability Control Data: Yaw Rate 173

Pre-crash Stability Control Data: Lateral Acceleration 175

Pre-crash Stability Control Data: Steering 175

Delta V Data 177

Accuracy Analysis 178Steady State Speed Data Testing 178

Hard Braking Speed Data Testing 178

Stability Control Data Testing 179

Summary and Conclusions 179References 180Acknowledgments 181Definitions/Abbreviations 182Appendix 183

Contents xi


Analysis of Crash Data from a 2012 Kia Soul Event Data Recorder 187

Introduction 188Literature Review 191Test Vehicles 192Data Collection Procedure 193

Methodology 193

Test Series 1 193

Test Series 2 194

Results 197Test Series #1 197

Test Series #2 199

Discussion 203Conclusions 206References 207Acknowledgments 208Glossary 208


EDR Pulse Component Vector Analysis 211Introduction 212Equipment 213

HYGE™ Acceleration-Type Sled System 213

Bosch CDR 214

Subject EDRs 214

Apparatus 215

Procedure 217

Initialization/Validation 217

Testing 217

Results 219

Yaw Test Results 220

Resultant Delta-V 220

Apparent Yaw Angle 221

RAM 1500 Delta-V Data Detail 221

Pitch Test Results 222

Discussion 223

Summary/Conclusions 223Further Research Opportunities 224References 224

xii Contents

Definitions/Abbreviations 225Appendix 226

Appendix A 226

Appendix B 227

Appendix C 228


Comparison of the Accuracy and Sensitivity of Generation 1, 2, and 3 Toyota Event Data Recorders in Low-Speed Collisions 229


ACMs 231

Instrumentation 231

Test Procedure 232

Data Reduction and Analysis 232

Results 233Repeatability 233

Trigger Threshold 234

Accuracy 235

Discussion 237Conclusions 240References 241Acknowledgments 242Appendix 243

Appendix A - Repeatability Data 243

Appendix B - Trigger Threshold Data 245

Appendix C - Full Model Regression Results 247

Appendix D - Residuals 249

V O L U M E 7 B — C H A P T E R 1 0

Event Data Recorder (EDR) Developed by Toyota Motor Corporation 251

Introduction 252 EDRs Developed by Toyota 253

Prior to EDR Regulations 253

Compliance with EDR Regulations 254

Addition of Pre-crash Data 255

Contents xiii

Post-crash Data Required for Crash Reconstruction 256Frontal Crash 256

Additional Side Crash Data Recording 258

Rollover Record 258

Recording of PUH Pedestrian Protection System 262

Recording by Non-crash Trigger 264

Download Tool 265

Automatic Collection of EDR Data 266 Trial of Advanced Automatic Collision Notification System 270Conclusion 274References 274Appendix 275

Appendix A - EDR Adoption Status in North America 275

Appendix B - Downloaded PUH System EDR Data 276

Appendix C - Trigger Items of VCH 276

Appendix D - VCH Data Example (2014 IS) 277

Appendix E - VCH Data Example (2014 IS) 277

Appendix F - Collected EDR Data Example 278


Longitudinal Delta V Offset Between Front and Rear Crashes in 2007 Toyota Yaris Generation 04 EDR 279

Introduction 280Testing Scope and Methodology 280Results 281Analysis 284Discussion 287Summary/Conclusions 289References 289Acknowledgments 290Definitions/Abbreviations 290Appendix 291

Appendix A 291

Appendix B 292

Appendix C 293

Appendix D 294

xiv Contents


A Compendium of Passenger Vehicle Event Data Recorder Literature and Analysis of Validation Studies 299

Introduction 300Body of Literature 301Data Selection 302Analysis: Precrash Data (Vehicle Speed) 303

Other Precrash Studies Not Analyzed 308

Analysis: Crash Data (Vehicle Velocity Change, ΔV ) 308Kia and Hyundai Vehicles Using the GIT Tool 309

Studies: Evaluation of Event Data Recorders in Full Systems Crash Tests (Niehoff, 2005) and Preliminary Evaluation of Advanced Air Bag Field Performance Using Event Data Recorders (Gabler, 2008) 310

Direct Contact Damage to the Module and Acceleration Clipping 311

Small or Partial Overlap Testing 311

Side Impact Testing 313

Side Pole Impact Testing 313

Impact and Velocity Change (ΔV ) Testing 315Automobile versus Pedestrian Testing 315

Automobile versus Motorcycle Testing 315

Low-Speed Vehicle-to-Vehicle and Vehicle-to-Barrier Testing 316

Vehicle to Heavy Truck Rear Underride Guard Testing 316

Crash Simulation Sled System Testing 316

Studies of Event Data Recorders on Vehicles in Japanese NCAP Crash Tests 317

Discussion 317Summary 318References 318Acknowledgments 321Appendix 322

Appendix A - Bibliography (All Studies) 322

Appendix B - Instrumented Testing Bibliography 334

Appendix C - Papers By Make, Year, and Model 340

Appendix D - Instrumented Testing Data Plots 345

Appendix E - Instrumented Testing Raw Data 354

Contents xv


An Analysis of EDR Data in Kawasaki Ninja 300 (EX300) Motorcycles 377

Introduction 378Testing Details 379Data Triggering 380Pre-emergency Shut-Down Data 385Power Loss Issues 387Summary/Conclusions 389References 390Definitions/Abbreviations 390Appendix 391

Appendix A: Sample EDR Event Data Table 391

Appendix B: EDR Flow Chart 394



Volume 8: Error Analysis and Uncertainty in Accident

Reconstruction



Introduction xi

C H A P T E R 1

Evaluating Uncertainty in Accident Reconstruction with Finite Differences 1

Introduction 2Mathematical Basis 2Data Sources 3Implementation 3Example 1: Simple Case 4Example 2: Finite Differences with A/R Software 8Example 3: Intersection Impact 9Conclusions 12Acknowledgments 12References 13Appendix A 14

Distance by Total Station 14

Distance 15

Arc 15

Angle 15

Right Angle 15

Weight 15

Mass Dispersion 15

Wheelbase 16

Tire-Road Friction, in situ 16

Tire-Road Friction, generic 16

Lateral Friction, generic 17

Post-Impact Unbraked Drag 17

Crush Depth 17

Crush Width 17

Crush Location 17

Crush Direction 17

Tiremark Measurement 18

contents

vi Contentsvi Contents

C H A P T E R 2

The Practical Application of Finite Difference Analysis in Accident Reconstruction 19

Introduction 20Exemplar Reconstruction 20

Forensic Task 20Reconstruction 20

Site and Vehicle Data 24Damage Data 24Output Data 24Site Plot 24Vector Plot 24

Results of Exemplar Reconstruction 25Finite Difference Analysis 25

Procedure 25Exemplar Deviations 25Deviation Summations 26Approach Speed Deviations 27

Component Deviations 28

Care In Measurement 29Transferability 29

Approach Analysis 29Approach analysis without FDA 30

Likely Approach Scenario without FDA 30Alternative Approach Scenario Without FDA 31

Approach Analysis With FDA 31Likely Approach Scenario with FDA 31Alternative Approach Scenario With FDA 32

Conclusions 34Acknowledgments 35References 35Appendix A: Accident Reconstruction Routines and Finite Difference Analysis 36Appendix B: Probable Uncertainties of Measurement 38

C H A P T E R 3

The Accuracy of Photogrammetry vs. Hands-On Measurement Techniques Used in Accident Reconstruction 39


Hands-On Measurement 42Photogrammetry Measurement 43Baseline Total Station Measurements 43

Contents vii Contents vii

Results 45Discussion 50Summary/Conclusions 52References 52Acknowledgments 54Appendix A 55

C H A P T E R 4

Considerations for Applying and Interpreting Monte Carlo Simulation Analyses in Accident Reconstruction 57

Introduction 58Calculations used for Comparison 58Selecting Input Distributions 59Determining the “Most Likely” Range for a Nonnormal Distribution 61Conclusion 63Acknowledgments 64References 64

C H A P T E R 5

Photogrammetric Measurement Error Associated with Lens Distortion 67

Introduction 68Background 68Testing Procedure 70Creating an Undistorted Image 70Manually Assessing Lens Distortion Coefficients in a Camera 72Sample Procedure 73Results of the Study 76Effect of Lens Distortion in Real-World Measurements 79Conclusions 81References 82Appendix A (Distortion Distance, per Camera, per Focal Length) 83Appendix B (Correction Coefficient Database) 118

viii Contentsviii Contents

C H A P T E R 6

Sensitivity of Monte Carlo Modeling in Crash Reconstruction 123

Introduction 124Probability Concepts 125

Distributions 125Mathematical Expectation 126

Probability of Excess 127

The Score Function Method 128Sensitivity of the Mean 128

Sensitivity of the Standard Deviation 129

Sensitivity of the Probability of Excess 130

Determining Kernel Functions 130

Univariate Normal Distribution 131

Bivariate Normal Distribution 131

Example of Energy from Residual Crush 132Problem Summary and Results 132

Convergence Study 133

Sensitivity of Results 135

Interpretation of Results 137


C H A P T E R 7

Monte Carlo Techniques for Correlated Variables in Crash Reconstruction 141

Introduction 142Probability Concepts 142

Multivariate Probability 142

Joint Correlated Distributions 142

Conditional and Marginal Distributions 144

Functions of Random Variables 146

Linear Combinations 147

Taylor Series Approximation 148

Test for Statistical Independence 148

The Monte Carlo Method 148

Modeling and Simulating Correlated Normal Variables 149Theory 149

Example of Determining Energy From Crush 150

Contents ix

Predicting Correlation 153Interpreting Correlated Results from a Monte Carlo Simulation 155Conclusions 158Acknowledgments 159References 159


Contents ix


Volume 9: Bicycle Accident Reconstruction



contents

Introduction xi

C H A P T E R 1

Use of Throw Distances of Pedestrians and Bicyclists as Part of a Scientific Accident Reconstruction Method 1

Introduction 2Basis of Speed Calculation 2New Results Based on Real Accidents 4

Kinematics of Impact 5

Relation between Throw Distances and Impact Speed 5Injury Relation to Impact Speed and Throw Distance 9Conclusion 11References 13

C H A P T E R 2

A Study of a Method for Predicting the Risk of Crossing-Collisions at Intersections 15

1. Introduction 162. Analysis of Traffic Accident Data 17

Breakdown of Crossing-Collisions 17

Combinations of Intersection Types and Accident Parties 18

Pre-crash Driving Patterns of Primary and Secondary Parties 19

3. Quantification of Crossing-Collision Risk 20Method of Estimating Crossing-Collision Risk 20

Method of Estimating P(A) for Individual Accident Factors 20

4. Estimation of Crossing-Collision Probabilities for Different Types of Intersections 21Estimation Method 21

Data Used and Estimated Results 22

5. Estimation Of Crossing-Collision Probabilities by Driving Pattern of Non-Right-Of-Way Vehicles 23Estimation Method 23


6. Estimation of Crossing-Collision Probabilities by Type of Other Vehicle 24Estimation Method 24


7. Estimation of Accident Reduction Effect of Various Safety Measures 25Estimation of the Effect of Infrastructure Implementation on Reducing Accidents 25

Estimation of the Effect of a Driver-Support System on Reducing Accidents 25

Comparison of Accident Reduction Effect of Infrastructure Implementation and Driver-Support System 27

8. Conclusions 27References 28

C H A P T E R 3

Road Bicycle Dynamics in the Presence of Idealized Roadway Irregularities 29

Introduction 29Literature Review 30Steady-State Cornering 30Modeling of Contacts with Irregularities 31Derivation of Pitchover Conditions 32Dynamics of Ramp Climbing 34Test Program 35

Bicycle Dynamics Over Idealized Roadway Irregularities 35

Conclusions 36References 36Nomenclature 38

C H A P T E R 4

Analysis of Bicycle Pitch-Over in a Controlled Environment 39

Introduction 40Defining Pitch-Over 40

Dynamics 41

Center of Gravity (CG) Location 41

Minimum Deceleration Required for Pitch-Over 41

vi Contents

vii Contents vii

Minimum Velocity 41

Instant Center of Rotation at Pitch-Over Initiation 42

Front Wheel Lift Off 42

Testing 42Setup 42

Bicyclist 43

Landing Zone 43

Load Plates 43

Sync Flash 44

Data Acquisition 44

Dowel Shooter 44

Video and Still Camera Documentation 44

Test Articles 45

Procedures 45

Error 46

Test Series 47

Brake Application 47

Dowel Insertion 47

Barrier Impact 47

Data Processing and Motion Analysis 47

Results 48Bicycle Damage 48

Brake Application Test Series 48

Dowel Insertion Test Series 50

Barrier Impact Test Series 53

Discussion 56Conclusion 57Acknowledgments 58References 58Appendix A - Bicycle Configuration 59

C H A P T E R 5

Influences on the Risk of Injury of Bicyclists’ Heads and Benefits of Bicycle Helmets in Terms of Injury Avoidance and Reduction of Injury Severity 61

Introduction 61Framework of Evaluation 65Documentation Method of GIDAS 66Descriptive Outcome Processing 66Accident and Injury Patterns of Bicyclists 66

Injury Severities of the Heads of Bicyclists Involved in an Accident 69Usage of Bicycle Helmets by Different Types of Bicyclists and In Relation to Different Accident Characteristics 70Effectiveness of the Bicycle Helmets 72Statistical Evaluation of the Influence of Different Parameters on Head Injuries 74Damage Pattern on the Helmet 75Conclusion 78References 79Acknowledgments 81

C H A P T E R 6

Wrap Around Distance (WAD) of Pedestrians and Bicyclists and Relevance as an Influence Parameter for Head Injuries 83

Introduction and Objectives 84Measurement of the WAD in Real Accidents 87Study Tasks 88Accident Studies Based on GIDAS 88Database 89Evaluation Structure of the Study 89A. Descriptive Analysis 90

A.1. Injury Severity Grade of the Head (AIS Head) 90

A.2. Direction of VRU Related to Driving Direction of the Car 92

A.3. Collision Speed of the Car 93

A.4. Head Impact Point—Lateral Distance to Longitudinal Car Axis 93

A.5. Head Impact Point—WAD 94

A.6. Influence of the Age of the VRU to the Injury Severity of the Head 94

B. Multivariate Analysis 95B.1. Statistical Analysis of Influence Importance of WAD,

Impact Speed of the Car, and Body Height and Age of the VRU for Head Injury Occurrence 96

Conclusion and Discussion 101References 102Acknowledgments 103

viii Contents

ix

C H A P T E R 7

Cycling Characteristics of Bicycles at an Intersection 105

Introduction 106Experiment Method 108

Site of the Investigation 108

Subjects of the Investigation 110

Investigation Items 110

The Extent to Which Traffic Regulations Were Observed 110

Cycling Characteristics of the Cyclists 110

The Velocity of the Cyclists 110

Trajectory 110

The Timing the Cyclists Stopped Pedaling 111

Method of Analysis 111

Results of the Experiment 111Percentage of Cyclists Who Confirmed Safety at the Intersection 111

The Percentage of Cyclists Coming to a Stop at the Intersection 112

Velocity of the Cyclists 113

Changes in the Bicycles’ Velocity when Entering into the Intersection 113

Trajectory of the Cyclists 115

Investigation of TTI 115

Timing of the Warning Given to Cyclists to Prevent a Collision 117

Conclusion and Discussion 1181. Confirming It Is Safe to Cross and Coming to a Stop at the

Intersection 118

2. Cyclist’ Velocity 119

3. Changes in Cyclists’ Speed when They Entered the Intersection 119

4. Bicycles’ Trajectory 119

5. Timing of the Warning to Prevent Collisions 119

References 120Acknowledgments 120


Contents ix


Volume 10A: Pedestrian Collisions



contents

Introduction xvii

V O L U M E 1 0 A — C H A P T E R 1

Investigation and Analysis of Real-Life Pedestrian Collisions 1


Background 5

Video Capture 5

Calibration 5

Data Analysis 6

Results 6Wrap Trajectories 6

Forward Projection Trajectories 8

Fender Vault Trajectories 9



Different Factors Influencing Post-Crash Pedestrian Kinematics 13

Introduction 14NASS-PCDS Analysis 15Principal Component Analysis 18Characteristics of Vehicle-Pedestrian Interaction 20Fe Analysis of Human Model 22

Adult Male 23

6-Year-Old Child 24

Ground-To-Head-Contact Distance 27Head Injury 29Standing Posture 31

Conclusions 32References 34Acknowledgments 36


Pedestrian Behavior at Signal-Controlled Crosswalks 37

Introduction 38Experimental Methodology 40

Experimental Setup 40

Data Acquisition 40

Results 42Perception/Reaction 42

Pedestrian Speeds 42

Conclusion 43Acknowledgments 44References 44


Throw Model for Frontal Pedestrian Collisions 45Introduction 46Pedestrian Impact Model 48

Throw Distance Model 48

Modeling of xL 50

Vehicle Motion 50

Throw Distance Index 50

Reconstruction Throw Model 51

Experimental Data 52Pedestrian Drag Factors 52

Experimental Values of Hill 52

Correction for Impact 52

Dummy Clothing Dependence 53

Experimental Throw Data 53

Preliminary Analysis of Experimental Data 53

Comparison of Model With Data 54

Reconstructed Wrap Collisions 55

Adult Dummy Wrap Collisions 57

Forward Projection Collisions 58

vi Contents

Contents vii

Roof Vault and Somersault Collisions 59

Fitting of the Reconstruction Model 59

Discussion and Conclusions 60Acknowledgment 61References 61


Pedestrian Throw Kinematics in Forward Projection Collisions 65


Pedestrian Dummy 67

Test Vehicles 67

Data Acquisition and Post Processing 68

Test Procedure 68

Results 69Forward Projection Trajectory: Dry Surface 69

Forward Projection Trajectory: Wet Surface 69

Forward Projection Throw Distance 70

Discussion 75Conclusion 76Acknowledgments 77References 77


Use of Throw Distances of Pedestrians and Bicyclists as Part of a Scientific Accident Reconstruction Method 79

Introduction 80Basis of Speed Calculation 80New Results Based on Real Accidents 82

Kinematics of Impact 83

Relation between Throw Distances and Impact Speed 83Injury Relation to Impact Speed and Throw Distance 87Conclusion 89References 91

viii Contents


Influence of Vehicle Body Type on Pedestrian Injury Distribution 93


Data Source 95

Inclusion and Exclusion 95

Injury Risk by Body Region and Vehicle Source 95

Results 95Injury by Body Region 95

Injury by Vehicle Component 96

LTVs 96

Cars 97

Discussion 98Injury Distribution by Body Region 98

Injury Distribution by Vehicle Source 98

Conclusion 99References 99Definitions, Acronyms, Abbreviations 100


Vehicle Lighting to Enhance Pedestrian Visibility 101

Introduction 101Pedestrian Vulnerability 102Detection Distance Requirements 102

Avoidance—Timing 102

Perception/Reaction Time Delay 102

The Temporal Bonus 103Time Needed to Walk Clear of Vehicle Path 104

Estimating the Temporal Bonus 104Driver-Reaction-Distance 106

Detection Distance Necessary to Avoid 106

Where is The Pedestrian? 106Pedestrian Lateral Location 106

Pedestrian Vertical Location 107

How Much Illumination? 107Discussion - Part I - The Good News 108Discussion - Part II - Some Alternatives 109

Contents ix

Conclusion 109Acknowledgments 110References 110Appendix A Pedestrian Location with Respect to Headlamps 111


Uncertainty Analysis of the Preimpact Phase of a Pedestrian Collision 113

Introduction 114Sensitivity to Uncertainty 114Maximum Uncertainty and Mean Square Uncertainty 116Monte Carlo Simulation 117Example and Discussion 117

Accident Scenario 117

Data 117

Accident Reconstruction. Time-Distance Analysis 118

Graphical Method 118Criterion of Driver’s Reaction Time Delay Evaluation 119

Analytical Method and Uncertainty Ranges 120Criterion of Driver’s Reaction Time Delay Evaluation 123

Monte Carlo Simulation 123Criterion of Driver’s Reaction Time Delay Evaluation 126

Comparison of Results 126


V O L U M E 1 0 A — C H A P T E R 10

Pedestrian Dummy Pelvis Impact Responses 129Introduction 130Materials and Method 130

Data for Biofidelity Evaluation of Dummy Pelvis Response 130

Lateral Loading Test to Isolated Pelvis by Salzar et al. 131

Response Corridor for Dummy Pelvis 132

Response Corridors Based on the Results from Salzar et al. 132

Estimation of rev.1 Dummy Pelvis 133rev.1 Dummy Pelvis Development 133

Validation of rev.1 Dummy Pelvis 135

Biofidelity Evaluation of the rev.1 Dummy Pelvis Against Salzar et al. 135

x Contents

Estimation of rev.2 Dummy Pelvis 136rev.2 Dummy Pelvis Development 136

Design of the rev.2 Dummy Pelvis 136

rev.2 Pelvis Preliminary Lateral Loading Test 137

Biofidelity Evaluation of the rev.2 Dummy Pelvis Against Preliminary Test 139

Biofidelity Evaluation of the rev.2 Dummy Pelvis Against Salzar et al. 140

Discussion 141Conclusion 145References 146Appendix A 147

Dummy Pelvis FE Model Development 147

Material Parameter Identification for Ilium (POM) 147

POM Material Model Validation 147

Material Parameter Identification for Pubic Symphysis (Rubber) 148

Rubber Material Model Validation 151

Quasi-static Lateral Compression Test for Isolated rev.1 Dummy Pelvis 151

Validation of rev.1 Dummy Pelvis FE Model 153



Volume 10B: Pedestrian Collisions



contents

Introduction xvii

V O L U M E 1 0 B — C H A P T E R 1

Design Style Influence on Pedestrian Leg Impacts 1

Introduction 1Legislative Activities 3

Biomechanics in Car Pedestrian Collision 4Tibia Injuries 4

Knee Joints 4

Dynamics of Lower Leg Pedestrian Impact 4Test Methods 4

Corner of Bumper 5

Lower Bumper Reference (LBR) Line 5

Bonnet Leading Edge (BLE) 6

Analyses Conditions 6Foam Absorber 7

Impact Bar and Crash Box 7

Lower Impact Bar 7

CAE Requirements and Input Data 9Analyses Results 9Conclusions 9References 10Additional Sources 10Definitions, Acronyms, Abbreviations 11


Age Effects on Injury Patterns in Pedestrian Crashes 13


Breakdown of Injury Diagnoses 21

Head Injuries 21

Torso Injuries 24

Pelvis and Lower Extremity 26

Pedestrian Injury Patterns 28

Head Injury 29

Torso and Upper Extremity Injury 30

Pelvis and Lower Extremity Injury 31

Discussion 32Head 32

Chest and Spine 33

Abdomen 34

Pelvis and Extremity Injury 35

Study Limitations 37



Injury Patterns among Special Populations Involved in Pedestrian Crashes 55



Head Injuries 62

Torso Injuries 67


Common Codiagnoses for the Intoxicated Population 69

Deaf Population 70

Blind Population 71

Intoxicated Population 72

Medical Device Population 73

Discussion 74Deaf Population 74

Blind Population 75

Intoxicated Population 76

Medical Device Population 79


Summary/Conclusions 81

vi Contents

Contents vii

References 81Acknowledgments 84Appendix 85


A Bayesian Approach to Cross-Validation in Pedestrian Accident Reconstruction 87

Introduction 88Reconstruction Model 90Evaluation Data 94Applying Model Checking/Criticism 94Taking a Closer Look 97Summary/Conclusion 98References 99Acknowledgments 101Appendix 101


Design of Lightweight Vehicle Front End Structure for Pedestrian Protection 103

Introduction 104Front End Module 104

Energy Absorber for Pedestrian Safety 105

Thermoplastic Pedestrian Safe Front End Structure 106Stage 1: Independent Design 106

Stage 2: Concurrent Evaluation of Acceptable Design Solution 107

Design of the Front End Module 108Thermoplastic-Based Solution for Pedestrian Safety 110Discussion 113References 113Definitions/Abbreviations 114


Modeling of Pedestrian Midblock Crossing Speed with Respect to Vehicle Gap Acceptance 115

Introduction 116Testing 116

Scene Description 116

viii Contents

Date/Time of Data Collection 117

Equipment Setup 117

Compiling the Data 117

Pedestrian Speed 117

Gap 119

Observations 120Data Modeling 122

Discussion 125Limitations and Future Work 126



Pedestrian Impact on Low-Friction Surface 129Introduction 130Discussion 130Methods 131Results 133Summary/Conclusions 136References 137Acknowledgments 138Appendix 139


A Novel Method for Daytime Pedestrian Detection 143

Introduction 144Literature Study 144Overview 145Segmentation 146

Edge Detection 146

Edge Linking 147

Single Pixel Disconnectivity 148

Color-Edge-Based Labeling 148

Detection 150Leg Detection 150

Head Detection 151

Summary/Conclusions 152References 155

Contents ix


Pedestrian Throw Distance Impact Speed Contour Plots Using PC-Crash 157

Introduction 158Pedestrian Kinematics 158

Pedestrian Collision Literature 158

Modeling 162PC-Crash 162

Vehicle Models 162

Methodology 1 162

Results 1 165

Methodology 2 167

Results 2 167

Discussion 168Limitations 168Future Work 168Conclusions 169Appendix 171

Appendix A 171

Appendix B 172

Appendix C1 173

Appendix C2 174

Appendix D1 175

Appendix D2 176

Appendix E1 177

Appendix E2 178

Appendix F 179

Appendix G 180

Appendix H 181

Appendix I 182

Appendix J 183

Appendix K 184

Appendix L 185

Appendix M 186

Appendix N 187

V O L U M E 1 0 B — C H A P T E R 1 0

Reconstruction of Vehicle-Pedestrian Collisions Including an Unknown Point of Impact 189

Introduction 190List of Variables 191

x Contents

Equations of Han-Brach Model 192Example Reconstruction Using Relative Rest Positions (Wrap Collision) 193Example Reconstruction Using Relative Rest Positions (Forward Projection Collision) 196Sensitivity of Reconstruction Variables: Throw Distance 197Sensitivity of Reconstruction Variables: Relative Distance to Rest 198Conclusions 199References 199



Volume 11: Biomechanics



contents

Introduction xvii

C H A P T E R 1

Biomechanics of Occupant Responses During Recreational Off-Highway Vehicle (ROV) Riding and 90-Degree Tip-Overs 1

Introduction 2Methods—Passive Response 3Methods—Active Response 5

Surrogates 5

Instrumentation 5

Off-Road Course 6

Roll Spit 6

Common Physical Activities 8

Data Analysis 8

Results and Discussion 9Passive Response 9

Active Response 13

90-Degree Rolls and Common Physical Activities 20

Conclusions 23References 24Acknowledgments 24

C H A P T E R 2

Comparative Study of Road Accidents in Iceland and Side Impact Compatibility 25

Introduction 26Road Accidents in Iceland 26

Fatal Side Impact Accidents 28

Finite Element Model 29Verification and Sensitivity of the Parameters 29

The Influence of Variation of HOF in Side Impacts 30The Effect of HOF on Compatibility in Side Impacts 31

Conclusion 31Acknowledgments 32References 32

C H A P T E R 3

Development of Numerical Models for Injury Biomechanics Research: A Review of 50 Years of Publications in the Stapp Car Crash Conference 33

Introduction 34Head Models 35

Lumped-Mass Models 35

Finite Element Models 36

Application of Models 44

Pediatric Brain Models 45

Other Head Component Models 46

Animal Head Models 46

Head Model Discussion 48

Simulating the Skull and Brain Junction 48

Skull Thickness 48

Injury Measures 49

Material Properties and Experimentally Measured Brain Responses 49

Neck Models 50Two-Joint Neck Models 51

Multibody (MB) Neck Models 51

FE Neck Models 51

Model Geometry 54

Material Properties 55

Muscle Simulation 55

Model Validation and Application 57

Thoracic Models 58Abdominal Models 64

Geometry 64


Model Application and Validation 65

Upper Extremities 68Geometry 68


Application and Validation 68

vi Contents

Lower Extremity Models the Pelvis 71Geometry 71



Ankle and Foot 72Geometry 72



Pedestrian and Frontal Impact Lower Extremity Models 78Geometry 78



Whole-Body Models 85Introduction 85

CAL/CAL3D Model 85

MVMA Models 85

MADYMO Dummy Models 86

MADYMO Whole-body Human Models 86

FE Dummy Model 87

FE Whole-Body Human Model 87

Discussion and Conclusions 90References 92

C H A P T E R 4

Threshold Time-to-Fire Determination for SRS to Control Occupant Injuries in Real-World Accidents 113


Work Process Flow 116

CAE Model Setup 116

Performance Parameters 116

Performance Verification Matrix 117

Results and Discussions 119Details 119

Correlation 119

Threshold Speed Determination 120

TTF Determination 121

Contents vii

Conclusions 123References 123Acknowledgments 124Appendix A Occupant Kinematics in Time Zone for no Fire Load Case 125Appendix B Occupant Kinematics in Time Zone for Threshold Fire Load Case 126Appendix C Estimation of Airbag Unfolding Pattern 127

C H A P T E R 5

Likelihood of Brain Injury in Motorcycle Accidents: A Comparison of Novelty and DOT-Approved Helmets 129


Test Helmets 131

Drop Tower and Instrumentation 131

Procedure 132

Data Analysis 132

Results 132Discussion 134

Comparison of Head-Forms 135


Style, Cost, and Comfort 136

Future Work 136

References 136

C H A P T E R 6

Small Occupant Neck Injury Biomechanics in Frontal Crash: A Study to Address the Variation in Restraint Performance with a Conventional 3-Point Single Loop Belt System 139


Model Overview 142

Model Validation 143

Sensitivity Analysis 144

viii Contents

Discussion 146Conclusions 150References 151Definitions/Abbreviations 153Appendix 153

Appendix A. Figure 10 from the text 153

Appendix B. Figure 12 from the text 153

Appendix C. Figure 20 from the text 154

C H A P T E R 7

Motion Capture Applications in Forensic Injury Accident Reconstruction 155

Introduction 155Motion Capture System and Setup 157Car Carrier Analysis 157

Methods 157

Results 159

Discussion 161

Asphalt Roller Analysis 161Methods 161

Results and Discussion 162

Summary 163Acknowledgments 163References 163

C H A P T E R 8

Predictors for Traumatic Brain Injuries Evaluated Through Accident Reconstructions 165


Human Head FE Model 168


Interface Conditions 173

Head Kinematics from NFL Reconstructions of Concussive I 173

Simulation of the Brain Response Using Head Kinematics from the NFL Reconstructions 174

Logistic Regression Analysis 174

Biomechanical Analysis of a MC Accident 177

Contents ix

Results 177Logistic Regression Analysis 179

Biomechanical Analysis of a MC Accident 183

Influence of Rotational and Translational Kinematics on the Intracranial Response 183

Influence of Effective Shear Stiffness for the Brain 185

Discussion 189Tissue Injury Predictors 189

Strain-Based Injury Predictors 189

Effective Stress 190

Strain Energy Density 190

Magnitude of Maximum and Minimum Pressure 190

Influence of Head Kinematics on the Intracranial Response 191

Head Kinematics-Based Predictors 191

Brain Shear Stiffness Dependency 194

Limitations 195

Conclusion 196Acknowledgments 197References 197Appendix 203

Appendix A–Curve Fitting of the Second-Order Ogden Model 203

Appendix B–Results from the Logistic Regression Analysis for all Regions and Tissue Injury Predictors 205

C H A P T E R 9

Senior Drivers, Bicyclists, and Pedestrian Behavior Related to Traffic Accidents and Injuries 209

Introduction 210Literature Review 210Accident Data Analysis of Road User’s Behavior 212

Car Drivers 213

Driving License 213

Seating Position 214

Safety Systems 214

Behavior 214

Bicycle 216

Safety Systems 217

Behavior 217

Pedestrian 219

x Contents

Contents xi

Discussion 220Conclusions 221References 222Acknowledgments 223Definitions/Abbreviations 223Appendix 224

C H A P T E R 1 0

Police Accident Report Restraint Usage Accuracy and Injury Severity 229

Introduction 229Methods 231Results 232Discussion 237Conclusion 240Acknowledgments 240References 240Definitions, Acronyms, Abbreviations 241Appendix 242

C H A P T E R 1 1

Occupant Injury in Motor Vehicle Crashes: Using Field Accident Data from Multiple Sources 245

Introduction 245Data Sources 246

National Automotive Sampling System (NASS) 246

General Estimates System (GES) 246

Crashworthiness Data System (CDS) 248

Fatality Analysis Reporting System (FARS) 248

Special Crash Investigations (SCI) 249

Crash Injury Research and Engineering Network (CIREN) 249

State Data Program (SDP) 249

State Data System (SDS) 249

Crash Outcome Data Evaluation System (CODES) 250

Large Truck Crash Causation Study (LTCCS) 250

Partners for Child Passenger Safety (PCPS) 250

xii Contents

Pedestrian Crash Data Study (PCDS) 251

National Electronic Injury Surveillance System (NEISS) 251

Nationwide Inpatient Sample (NIS) 251

National Hospital Discharge Survey (NHDS) 252

Medicare Database 253

National Ambulatory Medical Care Survey (NAMCS) 253

National Hospital Ambulatory Medical Care Survey (NHAMCS) 254

National Survey of Ambulatory Surgery (NSAS) 254

National Trauma Data Bank (NTDB) 254

Examples 255Discussion 256Conclusion 258Acknowledgments 258References 258Additional Sources 260Definitions, Acronyms, and Abbreviations 261Appendix A 262

ICD-9-Cm Codes 262

Supplementary Classification of External Causes of Injury and Poisoning (E-code) 262

C H A P T E R 1 2

Injury Risk to Specific Body Regions of Pedestrians in Frontal Vehicle Crashes Modeled by Empirical, In-Depth Accident Data 265

Introduction 266Literature Review 267Data and Methods 269

Study Data Characteristics 269

Coding of Variables and Treatment of Missing Data 270

Selection and Coding of Outcome (Target) Variables 270

Coding of Explanatory Variables 271

Treatment of Missing Explanatory Data 272

Statistical Methods 272

Results 274Pedestrian Injuries by Body Region 274

Overview of Injury Causing Components 276

Conditional Probability of Components, Given Injury Region 276

Conditional Probability of Injured Region, Given the Vehicle Component 278

Contents xiii

Outcome Variable Frequencies 282

Logistic Regression Analysis of Factors Influencing Injury Levels: Univariate Results 282

Analysis of Potential Confounders and Associations between Explanatory Variables 285

Logistic Regression Analysis of Factors Influencing Injury Levels: Multivariate Results 286

Performance of Multivariate Models 289

Discussion 290Injury severity and Mortality 290

Vehicle Components and Injuries 290

Factors Influencing Serious and Severe Injuries 290

Injury Multiplicity 291

Approach to a Comparative Evaluation Metric 291

Limitations and Future Research 292

Conclusions 293Acknowledgments 294References 294Appendix 298

C H A P T E R 13

Influences on the Risk of Injury of Bicyclists’ Heads and Benefits of Bicycle Helmets in Terms of Injury Avoidance and Reduction of Injury Severity 303

Introduction 303Framework of Evaluation 307Documentation Method of GIDAS 308Descriptive Outcome Processing 308Accident and Injury Patterns of Bicyclists 308Injury Severities of the Heads of Bicyclists Involved in an Accident 311Usage of Bicycle Helmets by Different Types of Bicyclists and in Relation to Different Accident Characteristics 312Effectiveness of the Bicycle Helmets 314Statistical Evaluation of the Influence of Different Parameters on Head Injuries 316Damage Pattern on the Helmet 317Conclusion 320References 321Acknowledgments 323

xiv Contents

C H A P T E R 14

Crash Injury Risks for Obese Occupants 325Introduction 326Methodology 326

NASS-CDS Analysis 326

Results 328NASS-CDS Analysis 328

Discussion 331Limitations 333References 333Appendix 335

C H A P T E R 15

Age Effects on Injury Patterns in Pedestrian Crashes 337



Head Injuries 345

Torso Injuries 348


Pedestrian Injury Patterns 352

Head Injury 353

Torso and Upper Extremity Injury 354

Pelvis and Lower Extremity Injury 355

Discussion 356Head 356

Chest and Spine 357

Abdomen 358

Pelvis and Extremity Injury 359



Contents xv

C H A P T E R 1 6

Characterization of Commercial Vehicle Crashes and Driver Injury 379


Construction of Analytical Data Files 382

Development of Crash Typology Tuned to Truck Driver Injury 382

Development of Distributions of Truck Driver Injury Severity 383

Example Cases from LTCCS 383

Results 383Vehicle Fleet 383

Crash Characterization 384

Example Case 388

Rollover 388

Frontal Crash 389

Truck Driver Injuries 389

Summary and Conclusions 389References 391Acknowledgments 392



Volume 12: Heavy Vehicle Event Data Recorder Interpretation



contents

Introduction xiii

C H A P T E R 1

Commercial Vehicle Event Data Recorders and the Effect of ABS Brakes During Maximum Brake Application 1


Tractor 2

Trailer 2

Instrumentation 2

Test Procedure 3

Data Reduction 3

Results 4Discussion 7Conclusion 10Acknowledgments 10References 11Appendix 11

C H A P T E R 2

Comparison of Heavy Truck Engine Control Unit Hard Stop Data with Higher-Resolution On-Vehicle Data 15

Introduction 16Research 16

Test Vehicle 16

Test Facility 16

Test Procedure 17

Recorded Data 17

ECU Data 18Analysis and Discussion 18

Baseline Dry Straight-Line Braking 18

Wet Stopping in Curve 20

Previously Published Data 21Conclusions 27Acknowledgments 27References 27Definitions, Acronyms, Abbreviations 28Appendix 29

C H A P T E R 3

A Statistical Analysis of Data from Heavy Vehicle Event Data Recorders 31


Defining Data Sets and Events 33

Analysis 34

Results 38Discussion 40Conclusion 40Acknowledgments 40References 41Appendix A 42Appendix B 43Appendix C 43Appendix D 44

C H A P T E R 4

Data Sources and Analysis of a Heavy Vehicle Event Data Recorder—V-MAC III 45

Introduction 45V-MAC III System 46

HVEDR Function 47

Vehicle Data Log 47

Incident Log 47

Vehicle Speed Calculation 47

Methods 48Test Location 48

Test Vehicle 48

vi Contents

Instrumentation 50

Methodology 50

Data Analysis 51Results 52

Driving Mode 52

Decel Mode 53

Uncertainty Analysis 53Conclusions 54Acknowledgments 54References 54Definitions, Acronyms, Abbreviations 55Appendix A 56

C H A P T E R 5

Method to Determine Vehicle Speed During ABS Brake Events Using Heavy Vehicle Event Data Recorder Speed 59

Introduction 59Vehicles 60Instrumentation 61Test Procedure 61Data Reduction 61Results 63Discussion 69Conclusions 69References 70Acknowledgments 70Appendix 71

C H A P T E R 6

Simulating the Effect of Collision-Related Power Loss on the Event Data Recorders of Heavy Trucks 75

Introduction 76Methodology 76Test Results 80

Detroit Diesel (DDEC IV and V) 80

Detroit Diesel and Mercedes (DDEC VI) 81

Contents vii

Mercedes (MBE) 82

CAT ADEM II and ADEM III 82

MACK V-MAC IV 84

Cummins ISM and ISX 85

Discussion 86Limitations 88Summary 89Conclusions 90References 90Abbreviations 91Acknowledgments 91Appendix A Summary of Results for all ECMs Tested 93Appendix B 94Appendix C 95Appendix D 96Appendix E 97

C H A P T E R 7

An Examination of Snapshot Data in Caterpillar Electronic Control Modules 99

Introduction 100Methodology 102Test Results 105

ADEM II (1994-1998 Engines) 105

5EK 3406E, 6TS 3406E, 9CK 3176B, 9NS C-12, 2PN C10 105

ADEM 2000 (1999-2001 ENGINES) 110

2WS 3406E, 6NZ C15, 2KS C12, 3CS C10 110

ADEM 2000 HEUI SERIES (1998-2001 ENGINES) 114

7AS 3126B 114

8YL 3126B, CKM 3126E 115

ADEM III (2002 “BRIDGE” ENGINES) 116

MBN C15, MBL C12, MBJ C10 116

ADEM III HEUI SERIES (2002 “BRIDGE” ENGINES) 117

HEP 3126E 117

ADEM III (2002-2006 ENGINES) 119

BXS C15, KCB C13, KCA C11 119

ADEM III HEUI SERIES (2002-2006 ENGINES) 120

9DG C9, KAL C7, SAP C7, WAX C7 120

viii Contents

ADEM IV (2005-2006 C15 ENGINES) 122

MXS C15, NXS C15 122

ADEM IV EPA07 (2007-NEWER ENGINES) 123

SAP C15, LEE C13 123

Limitations 125Summary/Conclusions 125References 127Acknowledgments 128Definitions/Abbreviations 129Appendix 130

C H A P T E R 8

Data Extraction Methods and Their Effects on the Retention of Event Data Contained in the Electronic Control Modules of Detroit Diesel and Mercedes-Benz Engines 133


DDEC-IV and DDEC-V—No Active Fault Codes 135

DDEC-IV and DDEC-V—With Active Fault Codes 136

MBE VCU/PLD 137

Summary of Results 137Conclusions 138Limitations 139References 139Acknowledgments 140Abbreviations 140Appendix A Tested Vehicles, Engines, and Engine Simulator 141Appendix B Testing Results 142

DDEC-IV—No Active Fault Codes 142

DDEC-IV—With Active Fault Codes 143

DDEC-V—No Active Fault Codes 144

DDEC-V—With Active Fault Codes 145

MBE VCU/PLD—No Active Fault Codes 147

MBE VCU/PLD—With Active Fault Codes 148

Contents ix

C H A P T E R 9

Timing and Synchronization of the Event Data Recorded by the Electronic Control Modules of Commercial Motor Vehicles—DDEC V 151

Introduction 152Methodology 153Results 156

Brake Pedal Time Lag 156

Clutch Pedal Time Lag 157

Accelerator (Throttle) Pedal Time Lag 157

Vehicle Speed and Engine Speed Time Lag 157

4PDT Switch Testing 158Timing and Synchronicity of J1939 Reported Data 161Discussion of Results 162

Brake Status 162

Clutch Status 163

Accelerator (Throttle) Pedal Position 163

4PDT Switch Testing 163

DDEC Reports Latency 164

Conclusions 166Limitations 169References 169Acknowledgments 169Definitions/Abbreviations 170Appendix 171

Appendix A: Instrumentation 171

Appendix B: Figures and Tables 171

C H A P T E R 1 0

Using Marine Engine Control Units in the Investigation of Watercraft Collision Incidents: Mercury Verado Outboard Engine 177

Introduction 178Marine Collision Investigation 178

Marine Propeller Slip 178

Marine Engine ECUs and EDR Data 179

x Contents

Contents xi

Methodology 180Laboratory Testing 181

Field Testing 182

Vessel Information 182

Test Descriptions 182

Test Results 183EDR Active Data Logging 183

EDR Active Register Set 183

EDR Data Verification 184

Powerloss Testing 185

Discussion and Conclusions 185Limitations 186References 187Acknowledgments 187Definitions and Abbreviations 187Appendix 188

Appendix A—Instrumentation 188

Appendix B—Test Results 188

C H A P T E R 1 1

Extracting Event Data from Memory Chips within a Detroit Diesel DDEC V 189

Introduction 190Case Study of a DDEC V 191

Inside the DDEC V 191

Exemplar ECM Data 192

Determining Data Meaning 193Data to Determine Identity 193

Data Used by DDEC Reports 194

Decoding Hard Brake and Last Stop Data 195

Determining Attribution Data for the Hard Brake and Last Stop Events 197

Determining the Daily Engine Usage Log Data 200

Discussion and Conclusions 201References 202Definitions/Abbreviations 202Acknowledgments 202

xii Contents

Appendix 203Appendix A: DDEC Reports Data from the Exemplar ECM 203

Appendix B: Last Stop Record from Exemplar ECM 205

Appendix C: Partial Daily Engine Usage Log from Exemplar ECM 206

Appendix D: HexEditor Screenshots for the Daily Engine Usage Log 207

Appendix E: Event Records from the Exemplar ECM Memory 210

Appendix F: Event Records from the Subject ECM Memory 213

Appendix G: Daily Engine Usage Log Interpretation 216

Appendix H: DDEC Reports Showing Negative Times 217

C H A P T E R 1 2

Recovery of Partial Caterpillar Snapshot Event Data Resulting from Power Loss 219

Introduction 220Previous Work 220

Motivating Example 221Vehicle Network Data 221

HVEDR Data 222

External Reference Instrumentation 223

Methodology 225Test Setup 226

ECM Power Relay 228

Retrieving Event Data 228

Network Log Analysis 228

Results and Discussion 230Limitations 231Conclusions 232References 232Definitions/Abbreviations 233Appendix 234

Appendix: Test Matrix 234


Documents

Collision Reconstruction Methodologies Volume 1: Collision