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Internal validation of near-crashes in naturalistic driving studies: a continuous and multivariate approach

Jenny Jonasson (Institutionen för matematiska vetenskaper, matematisk statistik ; SAFER - Fordons- och Trafiksäkerhetscentrum ) ; Holger Rootzén (Institutionen för matematiska vetenskaper, matematisk statistik)
Accident Analysis and Prevention (0001-4575). Vol. 62 (2014), p. 102-109.
[Artikel, refereegranskad vetenskaplig]

Large naturalistic driving studies give extremely detailed insight into how traffic accidents happen and what causes them. However, even in very large studies there are only relatively few crashes. Hence one additionally selects and studies crash surrogates, so called “near-crashes”, i.e. situations when a crash almost happened. The selection procedures invariably entail severe risks of causing bias. In this paper we use extreme value statistics to develop two methods to study the extent and form of this bias. The methods are applied to a large naturalistic driving study, the 100-car study. Both methods identified a severe discrepancy between the rear-striking near-crashes and the rear-striking crashes. Perhaps surprisingly, one conclusion is that, for rear-striking and in this study, the crashes have little relevance for increasing traffic safety. We believe substantial efforts should be made to develop statistical methods for using near-crashes and crashes in future large naturalistic driving studies (such as the SHRP2 study).

Nyckelord: Traffic safety, Rear-ending crash, Crash surrogate, Selection bias, Naturalistic driving study, Extreme value statistics



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Denna post skapades 2013-12-02. Senast ändrad 2015-03-10.
CPL Pubid: 188107

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)
SAFER - Fordons- och Trafiksäkerhetscentrum

Ämnesområden

Transport
Sannolikhetsteori och statistik
Farkostteknik

Chalmers infrastruktur