Literature DB >> 23259520

Analysis of the frequency and severity of rear-end crashes in work zones.

Yi Qi1, Raghavan Srinivasan, Hualiang Teng, Robert Baker.   

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 read-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.

Entities:  

Mesh:

Year:  2013        PMID: 23259520     DOI: 10.1080/15389588.2012.675109

Source DB:  PubMed          Journal:  Traffic Inj Prev        ISSN: 1538-9588            Impact factor:   1.491


  3 in total

1.  A mixture model with Poisson and zero-truncated Poisson components to analyze road traffic accidents in Turkey.

Authors:  Hande Konşuk Ünlü; Derek S Young; Ayten Yiğiter; L Hilal Özcebe
Journal:  J Appl Stat       Date:  2020-11-06       Impact factor: 1.416

Review 2.  A Systematic Review on the Role of Substance Consumption in Work-Related Road Traffic Crashes Reveals the Importance of Biopsychosocial Factors in Prevention.

Authors:  Sergio Frumento; Pasquale Bufano; Andrea Zaccaro; Anello Marcello Poma; Benedetta Persechino; Angelo Gemignani; Marco Laurino; Danilo Menicucci
Journal:  Behav Sci (Basel)       Date:  2022-01-25

3.  Assessment of Two-Vehicle and Multi-Vehicle Freeway Rear-End Crashes in China: Accommodating Spatiotemporal Shifts.

Authors:  Chenzhu Wang; Yangyang Xia; Fei Chen; Jianchuan Cheng; Zeng'an Wang
Journal:  Int J Environ Res Public Health       Date:  2022-08-18       Impact factor: 4.614

  3 in total

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