Error Analysis and Uncertainty in Accident Reconstruction / edited by Christopher Armstrong.

Format:

Book

Contributor:

Armstrong, Christopher (Accident reconstruction expert), editor.

Series:

Collision Reconstruction Methodologies

Collision Reconstruction Methodologies Series ; Volume 8

Language:

English

Subjects (All):

Traffic accident investigation--United States.

Traffic accident investigation.

Traffic accidents--Research.

Traffic accidents.

Automobiles--Collision damage.

Automobiles.

Traffic accidents--United States.

Error analysis (Mathematics).

Physical Description:

1 online resource (178 pages)

Edition:

First edition.

Place of Publication:

Warrendale, PA : SAE International, [2019]

Summary:

The last ten years have seen explosive growth in the technology available to the collision analyst, changing the way reconstruction is practiced in fundamental ways. The greatest technological advances for the crash reconstruction community have come in the realms of photogrammetry and digital media analysis. The widespread use of scanning technology has facilitated the implementation of powerful new tools to digitize forensic data, create 3D models and visualize and analyze crash vehicles and environments. The introduction of unmanned aerial systems and standardization of crash data recorders to the crash reconstruction community have enhanced the ability of a crash analyst to visualize and model the components of a crash reconstruction. Because of the technological changes occurring in the industry, many SAE papers have been written to address the validation and use of new tools for collision reconstruction. Collision Reconstruction Methodologies Volumes 1-12 bring together seminal SAE technical papers surrounding advancements in the crash reconstruction field. Topics featured in the series include: * Night Vision Study and Photogrammetry * Vehicle Event Data Recorders * Motorcycle, Heavy Vehicle, Bicycle and Pedestrian Accident Reconstruction The goal is to provide the latest technologies and methodologies being introduced into collision reconstruction - appealing to crash analysts, consultants and safety engineers alike.

Contents:

Cover

Table of Contents

Introduction

CHAPTER 1 Evaluating Uncertainty in Accident Reconstruction with Finite Differences

Mathematical Basis

Data Sources

Implementation

Example 1: Simple Case

Example 2: Finite Differences with A/R Software

Example 3: Intersection Impact

Conclusions

Acknowledgments

References

Appendix A

Distance by Total Station

Distance

Arc

Angle

Right Angle

Weight

Mass Dispersion

Wheelbase

Tire-Road Friction, in situ

Tire-Road Friction, generic

Lateral Friction, generic

Post-Impact Unbraked Drag

Crush Depth

Crush Width

Crush Location

Crush Direction

Tiremark Measurement

CHAPTER 2 The Practical Application of Finite Difference Analysis in Accident Reconstruction

Exemplar Reconstruction

Forensic Task

Reconstruction

Site and Vehicle Data

Damage Data

Output Data

Site Plot

Vector Plot

Results of Exemplar Reconstruction

Finite Difference Analysis

Procedure

Exemplar Deviations

Deviation Summations

Approach Speed Deviations

Component Deviations

Care In Measurement

Transferability

Approach Analysis

Approach analysis without FDA

Likely Approach Scenario without FDA

Alternative Approach Scenario Without FDA

Approach Analysis With FDA

Likely Approach Scenario with FDA

Alternative Approach Scenario With FDA

Appendix A: Accident Reconstruction Routines and Finite Difference Analysis

Appendix B: Probable Uncertainties of Measurement

CHAPTER 3 The Accuracy of Photogrammetry vs. Hands-On Measurement Techniques Used in Accident Reconstruction

Method

Hands-On Measurement

Photogrammetry Measurement

Baseline Total Station Measurements

Results

Discussion.

Summary/Conclusions

CHAPTER 4 Considerations for Applying and Interpreting Monte Carlo Simulation Analyses in Accident Reconstruction

Calculations used for Comparison

Selecting Input Distributions

Determining the "Most Likely" Range for a Nonnormal Distribution

Conclusion

CHAPTER 5 Photogrammetric Measurement Error Associated with Lens Distortion

Background

Testing Procedure

Creating an Undistorted Image

Manually Assessing Lens Distortion Coefficients in a Camera

Sample Procedure

Results of the Study

Effect of Lens Distortion in Real-World Measurements

Appendix A (Distortion Distance, per Camera, per Focal Length)

Appendix B (Correction Coefficient Database)

CHAPTER 6 Sensitivity of Monte Carlo Modeling in Crash Reconstruction

Probability Concepts

Distributions

Mathematical Expectation

Probability of Excess

The Score Function Method

Sensitivity of the Mean

Sensitivity of the Standard Deviation

Sensitivity of the Probability of Excess

Determining Kernel Functions

Univariate Normal Distribution

Bivariate Normal Distribution

Example of Energy from Residual Crush

Problem Summary and Results

Convergence Study

Sensitivity of Results

Interpretation of Results

CHAPTER 7 Monte Carlo Techniques for Correlated Variables in Crash Reconstruction

Multivariate Probability

Joint Correlated Distributions

Conditional and Marginal Distributions

Functions of Random Variables

Linear Combinations

Taylor Series Approximation

Test for Statistical Independence

The Monte Carlo Method.

Modeling and Simulating Correlated Normal Variables

Theory

Example of Determining Energy From Crush

Predicting Correlation

Interpreting Correlated Results from a Monte Carlo Simulation

About the Author.

Notes:

Includes bibliographical references.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

0-7680-9228-0

OCLC:

1302006520