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Technical Paper

Use of Monte Carlo Simulation Techniques in Accident Reconstruction

1994-03-01
940719
This paper describes a straight-forward, automated approach to performing sensitivity analyses using Monte Carlo simulation techniques. Probability distributions are assigned to key input parameters, and results are expressed in the form of probability distributions of each of the desired output parameters. ...The approach is fast and automated, and provides a rational basis for dealing with uncertainty and ranges of parameters in accident reconstruction analyses.
Technical Paper

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

2007-04-16
2007-01-0741
One popular method of examining and quantifying the uncertainty within an analysis is the use of Monte Carlo simulation techniques. The methods have been well established and published over the last several years by numerous authors. ...One of the key factors underlying the Monte Carlo analysis is the assumed probability distribution of the individual factors within the analysis. ...However, the literature to date has not examined how the assumption of a distribution affects the resulting probability distribution of the Monte Carlo analysis. This paper attempts to address this issue. Furthermore, with the large number of samples typically considered during a Monte Carlo analysis, the resulting probability distribution tends to be normal and lends itself well to statistical interpretation as to the “most likely” range of the desired parameter.
Journal Article

Sensitivity of Monte Carlo Modeling in Crash Reconstruction

2010-04-12
2010-01-0071
The Monte Carlo method is a well-known technique for propagating uncertainty in complex systems and has been applied to traffic crash reconstruction analysis. The Monte Carlo method is a probabilistic technique that randomly samples input distributions and then combines these samples according to a deterministic model. ...The Monte Carlo method is a well-known technique for propagating uncertainty in complex systems and has been applied to traffic crash reconstruction analysis. ...The computed sensitivity values were obtained using analytical derivatives which only required a single Monte Carlo simulation. The analytical derivative values are compared to a finite difference value to demonstrate numerical accuracy.
Technical Paper

Monte Carlo Simulation Methods Applied to Accident Reconstruction and Avoidance Analysis

1994-03-01
940720
In this paper Monte Carlo simulation methods are applied to accident reconstruction and accident avoidance analysis. ...When reconstructing vehicle accidents it is necessary in the course of the analysis to account for the uncertainty in the values of the key parameters such as tyre to road adhesion, the direction of vehicle movement both pre- and post-impact etc. ...Also the benefits which can be obtained from redundancy of the relationships describing the particular accident are examined. The results which can be obtained are demonstrated by a number of case studies.
Technical Paper

Application of the Monte Carlo Methods for Stability Analysis within the Accident Reconstruction Software PC-CRASH

2003-03-03
2003-01-0488
As in most accident reconstruction cases, several parameters, like ground friction or inter-vehicle friction are not well known, as well as many vehicle or driver related parameters. ...A method was developed, which allows one to vary multiple parameters based on a Monte Carlo method. The error within the fulfillment of the target function can thus easily be used as a quality indicator for the selected initial conditions. ...Two algorithms are presented, both based on the Monte Carlo approach. The first one serves as an alternative for the optimizer tool and is included in the current version of PC-Crash.
Journal Article

Monte Carlo Techniques for Correlated Variables in Crash Reconstruction

2009-04-20
2009-01-0104
Therefore, a discussion of uncertainty propagation techniques with correlation and Monte Carlo simulation of correlated variables is presented in this paper. The idea that measuring a parameter with a common instrument induces correlation is explored by examining the process of determining vehicle weights. ...However, the examples provided are aimed at introducing the concept of correlation in Monte Carlo simulation and determining the practical significance of correlation have yet to be determined. ...Furthermore, interpreting and presenting results from simple Monte Carlo analysis of a momentum problem requires using the concepts of joint, marginal, and conditional distributions to fully understand the results.
Technical Paper

Determination of Vehicle Velocities and Collision Location by Means of Monte Carlo Simulation Method

2006-04-03
2006-01-0907
“collision from the right-hand side of the center line” – “collision from the left-hand side of the center line”, or “the accident could have been avoided” – “the accident could not be avoided”). The aim of the paper was to present a method of collision reconstruction calculation using the principle of conservation of momentum, the principle of energy conservation, and the principle of kinetic energy and work equivalence (energy balance) (Marquard), taking into consideration Monte Carlo simulation method. ...The aim of the paper was to present a method of collision reconstruction calculation using the principle of conservation of momentum, the principle of energy conservation, and the principle of kinetic energy and work equivalence (energy balance) (Marquard), taking into consideration Monte Carlo simulation method. The applicability of the method in determination of distribution function for vehicle collision velocities was proved and, what is more important, its practical uselessness in determination of collision location. ...In road accident analysis the problem of uncertainty of calculation results becomes essential particularly when modification of input values within the adopted ranges leads to diametric change of the answer to the question posed by the court of justice (e.g.
Technical Paper

Integrating Monte Carlo Simulation, Momentum-Based Impact Modeling, and Restitution Data to Analyze Crash Severity

2001-10-01
2001-01-3347
Accurate evaluation of the crash severity will, therefore, include analysis of the effect that uncertainties in the values of the input parameters have on the calculated change in velocity. Monte Carlo simulation, a statistical technique, enables the reconstructionist to evaluate the effect of uncertainty on the analysis of crash severity. ...Use of the Monte Carlo simulation technique is beneficial since a reconstructionist can enter a range of values for each input parameter. ...Application of the Monte Carlo technique is intended to improve the legitimacy of crash severity analysis by helping the reconstructionist consider a wide range of possible solutions within the bounds of the imperfect data and report statistically meaningful ranges for the change in velocity.
Book

Collision Reconstruction Methodologies Volume 6A: Rollover Accident Reconstruction

2018-11-02
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. ...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.
Journal Article

A Bayesian Approach to Cross-Validation in Pedestrian Accident Reconstruction

2011-04-12
2011-01-0290
In statistical modeling, cross-validation refers to the practice of fitting a model with part of the available data, and then using predictions of the unused data to test and improve the fitted model. In accident reconstruction, cross-validation is possible when two different measurements can be used to estimate the same accident feature, such as when measured skidmark length and pedestrian throw distance each provide an estimate of impact speed. ...In accident reconstruction, cross-validation is possible when two different measurements can be used to estimate the same accident feature, such as when measured skidmark length and pedestrian throw distance each provide an estimate of impact speed. ...An actual measurement falling in an extreme tail of the predictive distribution suggests a weakness in the assumptions governing the reconstruction. This paper describes an implementation of these ideas using the Bayesian freeware WinBUGS.
Book

Collision Reconstruction Methodologies Volume 8: Error Analysis and Uncertainty in Accident Reconstruction

2018-11-02
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. ...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.
Technical Paper

On the Concept of Inter-Vehicle Friction and Its Application in Automobile Accident Reconstruction

2007-04-16
2007-01-0744
Occasionally, an accident reconstruction analyst is confronted with the task of reconstructing an accident with configurations that do not lend themselves to straightforward analytical methods. ...The analyst may often turn to accident reconstruction software such as the various versions of SMAC and some impulse-momentum approaches like PC-Crash and VCRware. ...This can lead to the modification of the inter-vehicle friction value to tune the simulation result; typically in an effort to force the final rest positions of the collision partners to match documented accident scene evidence. In this paper, the concept and application of the inter-vehicle friction coefficient is examined.
Journal Article

Probabilistic Reanalysis Using Monte Carlo Simulation

2008-04-14
2008-01-0215
PRA calculates very efficiently the system reliability or the average value of an attribute of a design for many probability distributions of the input variables, by performing a single Monte Carlo simulation. In addition, PRA calculates the sensitivity derivatives of the reliability to the parameters of the probability distributions.
Technical Paper

Using Multiple Processors for Monte Carlo Analysis of System Models

2008-04-14
2008-01-1221
Modeling variable physical parameters provides a better representation of what can be expected in production. Monte Carlo analysis is a standard method of simulating variability that occurs in real physical parameters. ...Automotive companies use Monte Carlo testing to ensure high quality, robust designs. Due to time and resource constraints, engineers often examine only a limited number of key parameters rather than an entire set. ...This paper presents new methods for distributing Monte Carlo analyses of system models across multiple machines. These methods reduce testing time and enable more complete analyses, ensuring better quality when designs go into production.
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