Abstract
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 language | English (US) |
|---|---|
| Pages (from-to) | 181-189 |
| Number of pages | 9 |
| Journal | Journal of Transportation Safety and Security |
| Volume | 1 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2009 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Accident reconstruction
- Bayesian inference
- Markov chain Monte Carlo
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