Sample-based bayesian accident reconstruction

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


In accident reconstruction, information derived from samples of crash tests can on occasion replace subjective prior information reflecting expert opinion. A method for accomplishing this, based on a straightforward application of Bayesian reasoning as used in statistics, is applied to three-accident scenarios: estimating critical speeds from yaw marks, estimating impact speed from crush, and estimating impact speed from pedestrian throw distance. The method is evaluated by comparing the estimates to measurements obtained in crash tests. In almost all cases the measured speeds were captured by the posterior 95% credible intervals.

Original languageEnglish (US)
Pages (from-to)181-189
Number of pages9
JournalJournal of Transportation Safety and Security
Issue number3
StatePublished - Sep 2009


  • Accident reconstruction
  • Bayesian inference
  • Markov chain Monte Carlo


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