Speed as a Risk Factor in Run-off Road Accidents: Bayesian Analysis with Differential Measurement Error

• Activity Number: 314
• Type: Contributed
• Date/Time: Wednesday, August 11, 2004 : 9:00 AM to 10:50 AM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Gary A. Davis*+
• Companies: University of Minnesota
• Keywords: Markov chain Monte Carlo ; accident reconstruction ; traffic safety ; Bayesian methods ; logistic regression

Abstract

Research done in the 1960s and 1970s suggested that road accident risk is a U-shaped function of speed, with risk increasing as one travels both faster and slower than what is average on a road. Debate continues as to the causes of this relationship, and there is reason to suspect that it may be an artifact of measurement error or mixing of different accident types. This paper describes two case-control analyses of run-off road accidents, one using data collected in Adelaide, Australia, and one using data from Minnesota. In both analyses the speeds of the case vehicles were estimated using accident reconstruction, while the speeds of the controls were measured on vehicles travelling the accident site under similar conditions. Bayesian relative risk regression was used to relate speed to accident risk, and uncertainty in the case speeds was accounted for by treating these as additional unknowns with informative priors. Neither dataset supported the existence of a U-shaped relationship, although accident risk clearly tended to increase as speed increased.