Highlights ► The paper proposes a new method for conducting case-control meta-analyses. ► The method is applied to studies of the effects of electronic stability control. ► The validity of the method is tested and confirmed. ► It provides more rapid and precise estimates of crash effectiveness.
Abstract Real-world retrospective evaluation of the safety benefits of new integrated safety technologies is hampered by the lack of sufficient data to assess early reliable benefits. This MUNDS study set out to examine if a “prospective” case-control meta-analysis had the potential to provide more rapid and rigorous analyses of vehicle and infrastructure safety improvements. To examine the validity of the approach, an analysis of the effectiveness of ESC using a consistent analytic strategy across 6 European and Australasian databases was undertaken. It was hypothesised that the approach would be valid if the results of the MUNDS analysis were consistent with those published earlier (this would confirm the suitability of the MUNDS approach). The findings confirm the hypothesis and also found stronger and more robust findings across the range of crash-types, road conditions, vehicle sizes and speed zones than previous. The study recommends that while a number of limitations were identified with the findings that need be addressed in future research, the MUNDS approach nevertheless should be adopted widely for the benefit of all vehicle occupants.
Evaluation of the benefits of vehicle safety technology: The MUNDS study
Accident Analysis and Prevention ; 55 ; 274-281
2013-02-20
8 pages
Article (Journal)
Electronic Resource
English
Evaluation of the benefits of vehicle safety technology: The MUNDS study
Online Contents | 2013
|Benefits from NASA-developed technology: Safety
NTRS | 1972
Emissions benefits of emerging vehicle technology
Tema Archive | 1998
|Evaluation of Safety Benefits from a Heavy-Vehicle Forward Collision Warning System
Online Contents | 2010
|Evaluation of Safety Benefits from a Heavy-Vehicle Forward Collision Warning System
Transportation Research Record | 2010
|