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Title:

Method for the Use of Naturalistic Driving Study Data to Analyze Rear-End Crash Sequences

Accession Number:

01552345

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States
Order URL: http://www.trb.org/main/blurbs/173968.aspx

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Order URL: http://worldcat.org/isbn/9780309369596

Abstract:

Many factors are associated with crash risk, but their contribution to the progression of a crash is often unclear. Research on and understanding of the crash sequence are needed. One of the advantages of studying crash sequence is to identify the causative chain of crashes and, subsequently, the identification of effective countermeasures that may feasibly mitigate crash risk. An analogy to epidemiological studies is particularly useful: although researchers confirm that many factors are associated with an increase in the probability of myocardial infarction, there is still a need to research the disease process, the physiological process that promotes disease growth, and the possible interventions to treat or even prevent the disease. This study used data from the Integrated Vehicle-Based Safety System program. Two freeway rear-end events, including one crash and one near crash, with similar crash sequences were studied. The crash sequences of the two events were as follows: (a) the drivers maintained a temporal headway of less than 1 s at the beginning; (b) the traffic flow conditions were likely to cause misjudgments by the drivers and result in glances in inappropriate directions; (c) when the drivers were distracted, the leading vehicle decelerated; (d) the drivers did not decelerate accordingly and had their feet on the accelerator pedal; and (e) one event resulted in a crash and the other in a near crash. This study highlighted an approach for comparing and dissecting the differences in the crash sequence that led to the different outcomes.

Monograph Accession #:

01595985

Report/Paper Numbers:

15-4030

Language:

English

Authors:

Wu, Kun-Feng
Thor, Craig P

Pagination:

pp 27–36

Publication Date:

2015

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2518
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309369596

Media Type:

Print

Features:

Figures (6) ; Photos; References (47)

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors

Files:

TRIS, TRB, ATRI

Created Date:

Dec 30 2014 1:19PM

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