Analysis of the Frequency and Severity of Rear-End Crashes in Work Zones

Document Type

Article

Publication Date

2013

Publication Title

Traffic Injury Prevention

Volume

14

Issue

1

First page number:

61

Last page number:

72

Abstract

OBJECTIVE:

The objective of this study was to identify the factors that influence the frequency and severity of rear-end crashes in work zones because rear-end crashes represent a significant proportion of crashes that occur in work zones.

METHODS:

Truncated count data models were developed to identify influencing factors on the frequency of rear-end crashes in work zones and ordered probit models were developed to evaluate influencing factors on the severity of rear-end crashes in work zones.

RESULTS:

Most of the variables identified in this study for these 2 models were significant at the 95 percent level. The statistics for models indicate that the 2 developed models are appropriate compared to alternative models.

CONCLUSIONS:

Major findings related to the frequency of rear-end crashes include the following: (1) work zones for capacity and pavement improvements have the highest frequency compared to other types of work zones; (2) work zones controlled by flaggers are associated with more rear-end crashes compared to those controlled by arrow boards; and (3) work zones with alternating one-way traffic tended to have more rear-end crashes compared to those with lane shifts. Major findings related to the severity of the rear-end crashes include the following: (1) rear-end crashes associated with alcohol, night, pedestrians, and roadway defects are more severe, and those associated with careless backing, stalled vehicles, slippery roadways, and misunderstanding flagging signals are less severe; (2) truck involvement and a large number of vehicles in a crash are both associated with increased severity, and (3) rear-end crashes that happened in work zones for bridge, capacity, and pavement are likely to be more severe than others.

Keywords

Accidents; traffic/Statistics & numerical data; Automobiles; Environment design/Statistics & numerical data; Humans; Men; Models; statistical; Regression analysis; Risk assessment; Risk factors; Road work zones; Traffic accidents; Women; Workplace

Disciplines

Transportation

Language

English

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

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