Traffic accident risk perception among drivers: a latent variable approach

Thomas E. Guerrero, Juan de Dios Ortuzar and Sebastian Raveau

Transportation Planning and Technology, 2020, vol. 43, issue 3, 313-324

Abstract: Governments require decision tools to deal with road traffic accidents, a pandemic resulting in millions of deaths around the world. Evidence shows that human factors are one of the major causes of road accidents, and there is much interest in identifying variables that may have an impact on drivers’ perception of risk. To this aim, we design a stated choice experiment with eight hypothetical driving scenarios considering attributes that have been strongly associated with increased accident risks: (i) driving speed, (ii) driving the wrong way in a one-way street, (iii) overtaking on a bend, and (iv) driving under the influence of alcohol or drugs. Data from a sample of survey respondents are used to estimate a hybrid discrete choice model incorporating two latent variables, Driver Concentration and Safe Driving. Our results may contribute to the design of public policies geared to prevent accidents by encouraging safer driving behaviour.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03081060.2020.1735763 (text/html)
Access to full text is restricted to subscribers.

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:taf:transp:v:43:y:2020:i:3:p:313-324

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GTPT20

DOI: 10.1080/03081060.2020.1735763

Access Statistics for this article

Transportation Planning and Technology is currently edited by Dr. David Gillingwater

More articles in Transportation Planning and Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().