Contextual ranking by passive safety of generational classes of light vehicles

Z. Ouni, C. Denis, C. Chauvel and A. Chambaz

Journal of the Royal Statistical Society Series C, 2018, vol. 67, issue 2, 395-416

Abstract: Each year, the Bulletin d’Analyse des Accidents Corporels (BAAC) data set gathers descriptions of traffic accidents on French public roads involving one or several light vehicles and injuring at least one of the passengers. Each light vehicle can be associated with its ‘generational class’ (GC), a raw description of the vehicle including its date of design, date of entry into service and size class. In two given contexts of accident, two light vehicles with two different GCs do not necessarily offer the same level of safety to their passengers. The objective of this study is to assess to what extent more recent generations of light vehicles are safer than older vehicles on the basis of the BAAC data set. We rely on ‘scoring’: we look for a score function that associates any context of accident and any GC with a real number in such a way that, the smaller is this number, the safer is the GC in the given context. A better score function is learned from the BAAC data set by cross‐validation, under the form of an optimal convex combination of score functions produced by a library of ranking algorithms by scoring. An oracle inequality illustrates the performances of the resulting meta‐algorithm. We implement it, apply it and show some results.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/rssc.12232

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:67:y:2018:i:2:p:395-416

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().