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Sample-Based Estimation of Vehicle Speeds from Yaw Marks: Bayesian Implementation Using Markov Chain Monte Carlo Simulation
Technical Paper
2014-01-0467
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The critical speed method uses measurements of the radii of yawmarks left by vehicles, together with values for centripetal acceleration, to estimate the speeds of the vehicles when the yawmarks were made. Several field studies have indicated that equating the centripetal force with braking friction produced biased estimates, but that the biases tended to be small (e.g. within 10%-15% on average) and led to underestimates, suggesting that the method can be useful for forensic purposes. Other studies, however, have challenged this conclusion. The critical speed method has also seen use in safety-related research, where it is important to have a reliable assessment of the uncertainty associated with a speed estimate. This paper describes a variant of the critical speed method, where data from field tests lead to an informative prior probability distribution for the centripetal acceleration. Using Bayes theorem, this distribution is combined with the measured radius to produce a posterior probability distribution for the desired speed. The required computations are readily carried out using Markov Chain Monte Carlo simulation. Calibration/Cross-validation tests, conducted using published data sets, in most cases found no significant differences between the actual and the nominal coverages of confidence intervals. For example, the 90% confidence intervals computed from the measured yaw radii tended to catch approximately 90% of the measured vehicle speeds.
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Citation
Davis, G., "Sample-Based Estimation of Vehicle Speeds from Yaw Marks: Bayesian Implementation Using Markov Chain Monte Carlo Simulation," SAE Technical Paper 2014-01-0467, 2014, https://doi.org/10.4271/2014-01-0467.Also In
References
- Fricke , L. Traffic Crash Reconstruction 2 nd Northwestern University Center for Public Safety Evanston, IL 2010
- Lindley , D. Subjective Probability, Decision Analysis, and Their Legal Consequences Journal of the Royal Statistical Society A 154 1991 83 92
- Taroni , F. , and Bierdermann , A. Inference Problems in Forensic Science Bayesian Networks: A Practical Guide to Applications Pourret , O. , Naim , P. , and Marcot , B. Wiley New York 2008 113 126
- Brach , R. Uncertainty in Accident Reconstruction Calculations SAE Technical Paper 940722 1994 10.4271/940722
- Knott , A. ‘Probable Speed Analysis' Statistical Modeling of Auto Accidents vs. Deterministic Modeling Journal of the National Academy of Forensic Engineers 10 1993 15 26
- Ball , J. , Danaher , D. , and Ziernicki , R. Considerations for Applying and Interpreting Monte Carlo Simulation Analyses in Accident Reconstruction SAE Technical Paper 2007-01-0741 2007 10.4271/2007-01-0741
- Davis , G. Sample-Based Bayesian Reconstruction of Road Accidents Journal of Transportation Safety and Security 1 2009 181 189
- Kloeden , C. , McLean , J. , Moore , V. , and Ponte , G. Traveling Speed and the Risk of Crash Involvement NHMRC Road Accident Research Unit, University of Adelaide Adelaide, Australia 1997
- Shinar , D. Traffic Safety and Human Behavior Elsevier Amsterdam 2007
- Draper , D. Bayesian Model Specification: Heuristics and Examples Bayesian Theory and Applications Damien P. , Dellaportas P. , Polson N. , and Stephens D. Oxford Press 2013
- Brach , R.M. and Brach , M. Vehicle Accident Analysis and Reconstruction Methods Sectond SAE International Warrendale, PA 978-0-7680-3437-0 2011 10.4271/R-397
- Daily , J. , Shigemura , N. and Daily , J. Fundamentals of Traffic Crash Reconstruction IPTM Jacksonville, FL 2013
- Richardson , S. , Orton , T. , Josevski , N. , Pok , W. et al. A Critique of Critical Speed Yaw Mark Research SAE Technical Paper 2012-01-0600 2012 10.4271/2012-01-0600
- Lambourn , R. The Calculation of Motor Car Speeds from Curved Tire Marks Journal of the Forensic Science Society 29 1989 371 386
- Semon , M. Determination of Speed from Yawmarks Forensic Accident Investigation: Motor Vehicles Bohan T. and Damask A. Michie Butterworth Charlottesville, VA 1995
- Brach , R. An Analytical Assessment of the Critical Speed Formula SAE Technical Paper 970957 1997 10.4271/970957
- Bellion , P. Project Y.A.M. (Yaw Analysis Methodology) Vehicle Testing and Findings - Victoria Police, Accident Investigation Section SAE Technical Paper 970955 1997 10.4271/970955
- Cliff , W. , Lawrence , J. , Heinrichs , B. , and Fricker , T. Yaw Testing of an Instrumented Vehicle with and without Braking SAE Technical Paper 2004-01-1187 2004 10.4271/2004-01-1187
- Amirault , G. and MacInnis , S. Variability of Yaw Calculations from Field Testing SAE Technical Paper 2009-01-0103 2009 10.4271/2009-01-0103
- Sledge , N. and Marshek , K. Formulas for Estimating Vehicle Critical Speed From Yaw Marks - A Review SAE Technical Paper 971147 1997 10.4271/971147
- Dickerson , C. , Arndt , M. , Arndt , S. , and Mowry , G. Evaluation of Vehicle Velocity Predictions Using the Critical Speed Formula SAE Technical Paper 950137 1995 10.4271/950137
- Fischer , W. Challenging the Critical Speed Formula In Light Of the Daubert Decision SAE Technical Paper 2005-01-3141 2005 10.4271/2005-01-3141
- Wach , W. Uncertainty in Calculations Using Lambourn's Critical Speed Procedure SAE Technical Paper 2013-01-0779 2013 10.4271/2013-01-0779
- Davis , G. , Davuluri , S. , and Pei , J. Speed As a Risk Factor in Serious Run-off-Road Crashes: Bayesian Case-Control Analysis with Case Speed Uncertainty Journal of Transportation and Statistics 9 1 2006 17 28
- Kloeden , C. , McLean , J. , and Glonek , G. Reanalysis of Traveling Speed and the Risk of Crash Involvement in Adelaide South Australia Road Accident Research Unit, University of Adelaide Adelaide, Australia 2002
- Bartlett , W. , Wright , W. , Masory , O. , Brach , R. et al. Evaluating the Uncertainty in Various Measurement Tasks Common to Accident Reconstruction SAE Technical Paper 2002-01-0546 2002 10.4271/2002-01-0546
- Lunn , D. , Thomas , A. , Best , N. , and Spiegelhalter , D. WinBUGS-A Bayesian Modeling Framework: Concepts, Structure, and Extensibility Statistics and Computing 10 2000 325 337
- Road Test Digest Car and Driver 50 10 April 2005 146 147