Relative risk of causing a road traffic crash: Quasi-induced exposure approach and its possible biases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F19194951%3A_____%2F25%3AN0000005" target="_blank" >RIV/19194951:_____/25:N0000005 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11220/25:10500507

Výsledek na webu

<a href="https://www.istiee.unict.it/sites/default/files/files/ET_2025_102_6.pdf" target="_blank" >https://www.istiee.unict.it/sites/default/files/files/ET_2025_102_6.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Relative risk of causing a road traffic crash: Quasi-induced exposure approach and its possible biases

Popis výsledku v původním jazyce

This paper addresses the challenge of heterogeneity in risk exposure when estimating the relative risk (RR) of causing road traffic crashes (RTCs) for different driver types. Quasi-induced exposure is a well-established alternative to direct data collection for exposure estimation. We investigate biases imposed on RR estimates causedby errors in fault assignment and unequal driver mix. Simulations reveal the directions and magnitudes of the possible biases and empirical tests of these biases are performed on a Czech dataset (1.2 million RTCs). Results show that errors in responsibility assignment work in opposite directions, with magnitude of bias depending on the size of the error and the target group proportion. Bias caused by unequal mixing depends on the target group proportion and the extent of the heterogeneity of not-at-fault drivers. Empirical tests confirm the discussed biases and underline their importance while interpreting RR estimates, so far mostly ignored by the literature.

Název v anglickém jazyce

Relative risk of causing a road traffic crash: Quasi-induced exposure approach and its possible biases

Popis výsledku anglicky

This paper addresses the challenge of heterogeneity in risk exposure when estimating the relative risk (RR) of causing road traffic crashes (RTCs) for different driver types. Quasi-induced exposure is a well-established alternative to direct data collection for exposure estimation. We investigate biases imposed on RR estimates causedby errors in fault assignment and unequal driver mix. Simulations reveal the directions and magnitudes of the possible biases and empirical tests of these biases are performed on a Czech dataset (1.2 million RTCs). Results show that errors in responsibility assignment work in opposite directions, with magnitude of bias depending on the size of the error and the target group proportion. Bias caused by unequal mixing depends on the target group proportion and the extent of the heterogeneity of not-at-fault drivers. Empirical tests confirm the discussed biases and underline their importance while interpreting RR estimates, so far mostly ignored by the literature.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50703 - Transport planning and social aspects of transport (transport engineering to be 2.1)

Projekt

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Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

European Transport Trasporti Europei

ISSN

1825-3997

e-ISSN

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Svazek periodika

neuveden

Číslo periodika v rámci svazku

102

Stát vydavatele periodika

IT - Italská republika

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

001544945400005

EID výsledku v databázi Scopus

2-s2.0-105013125933