
Error Analysis and Uncertainty in Accident Reconstruction
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Content
- Cover
- Table of Contents
- Introduction
- CHAPTER 1 Evaluating Uncertainty in Accident Reconstruction with Finite Differences
- Introduction
- 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
- Introduction
- 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
- Conclusions
- Acknowledgments
- References
- 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
- Introduction
- Method
- Hands-On Measurement
- Photogrammetry Measurement
- Baseline Total Station Measurements
- Results
- Discussion
- Summary/Conclusions
- References
- Acknowledgments
- Appendix A
- CHAPTER 4 Considerations for Applying and Interpreting Monte Carlo Simulation Analyses in Accident Reconstruction
- Introduction
- Calculations used for Comparison
- Selecting Input Distributions
- Determining the "Most Likely" Range for a Nonnormal Distribution
- Conclusion
- Acknowledgments
- References
- CHAPTER 5 Photogrammetric Measurement Error Associated with Lens Distortion
- Introduction
- 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
- Conclusions
- References
- Appendix A (Distortion Distance, per Camera, per Focal Length)
- Appendix B (Correction Coefficient Database)
- CHAPTER 6 Sensitivity of Monte Carlo Modeling in Crash Reconstruction
- Introduction
- 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
- Conclusion
- References
- Acknowledgments
- CHAPTER 7 Monte Carlo Techniques for Correlated Variables in Crash Reconstruction
- Introduction
- Probability Concepts
- 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
- Conclusions
- Acknowledgments
- References
- About the Author
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