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Identification of Influential Factors and Potentially Hazardous Location of Rear-End Collisions with Hard-Braking Events Data.

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Title: Identification of Influential Factors and Potentially Hazardous Location of Rear-End Collisions with Hard-Braking Events Data.
Authors: Choe, Cheol-Won1 (AUTHOR) stlcww@mju.ac.kr, Kim, Ducknyung2 (AUTHOR) k999@ex.co.kr, Kim, Seung-Min3 (AUTHOR) khh9292@mju.ac.kr, Park, Ho-Chul4 (AUTHOR) hcpark@mju.ac.kr
Source: Journal of Transportation Engineering. Part A. Systems. Aug2026, Vol. 152 Issue 8, p1-10. 10p.
Subjects: Traffic accidents, Negative binomial distribution, Motor vehicle driving, Safety, Traffic safety, Traffic accident investigation
Abstract: Rear-end collisions on expressways account for approximately 43% of the total collision cases, which is a high proportion. Extensive research has been conducted on rear-end collisions on expressways using traffic collision data. However, because traffic collisions occur rarely and randomly, it is challenging to conduct comprehensive traffic safety-related analyses using collision data only. Surrogate safety measures (SSM) can be used to replace collision data, but they also face challenges in constructing extensive data beyond spatial and temporal constraints. Hard-braking event data used in this study were collected primarily from smartphones or navigation applications installed in vehicles, which allowed us to obtain data from all timeframes on nationwide expressways. Hard-braking events exhibit a strong association with rear-end collisions, and are considered precollision indicators. This research developed negative binomial models for hard-braking events and rear-end collisions, and computed segment-level potential for safety improvement (PSI). High-risk segments are identified by clustering elevated PSI for hard-braking events and, separately, for rear-end collisions, and contributing factors were examined. The findings demonstrate the value of hard-braking events for screening hazardous locations and informing preventive safety strategies on expressways. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Transportation Engineering. Part A. Systems is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 194607069
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Identification of Influential Factors and Potentially Hazardous Location of Rear-End Collisions with Hard-Braking Events Data.
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  Data: <searchLink fieldCode="AR" term="%22Choe%2C+Cheol-Won%22">Choe, Cheol-Won</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> stlcww@mju.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Ducknyung%22">Kim, Ducknyung</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> k999@ex.co.kr</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Seung-Min%22">Kim, Seung-Min</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> khh9292@mju.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Park%2C+Ho-Chul%22">Park, Ho-Chul</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> hcpark@mju.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Transportation+Engineering%2E+Part+A%2E+Systems%22">Journal of Transportation Engineering. Part A. Systems</searchLink>. Aug2026, Vol. 152 Issue 8, p1-10. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Traffic+accidents%22">Traffic accidents</searchLink><br /><searchLink fieldCode="DE" term="%22Negative+binomial+distribution%22">Negative binomial distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+vehicle+driving%22">Motor vehicle driving</searchLink><br /><searchLink fieldCode="DE" term="%22Safety%22">Safety</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+safety%22">Traffic safety</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+accident+investigation%22">Traffic accident investigation</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Rear-end collisions on expressways account for approximately 43% of the total collision cases, which is a high proportion. Extensive research has been conducted on rear-end collisions on expressways using traffic collision data. However, because traffic collisions occur rarely and randomly, it is challenging to conduct comprehensive traffic safety-related analyses using collision data only. Surrogate safety measures (SSM) can be used to replace collision data, but they also face challenges in constructing extensive data beyond spatial and temporal constraints. Hard-braking event data used in this study were collected primarily from smartphones or navigation applications installed in vehicles, which allowed us to obtain data from all timeframes on nationwide expressways. Hard-braking events exhibit a strong association with rear-end collisions, and are considered precollision indicators. This research developed negative binomial models for hard-braking events and rear-end collisions, and computed segment-level potential for safety improvement (PSI). High-risk segments are identified by clustering elevated PSI for hard-braking events and, separately, for rear-end collisions, and contributing factors were examined. The findings demonstrate the value of hard-braking events for screening hazardous locations and informing preventive safety strategies on expressways. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Journal of Transportation Engineering. Part A. Systems is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1061/JTEPBS.TEENG-9181
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      – Code: eng
        Text: English
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        PageCount: 10
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      – SubjectFull: Traffic accidents
        Type: general
      – SubjectFull: Negative binomial distribution
        Type: general
      – SubjectFull: Motor vehicle driving
        Type: general
      – SubjectFull: Safety
        Type: general
      – SubjectFull: Traffic safety
        Type: general
      – SubjectFull: Traffic accident investigation
        Type: general
    Titles:
      – TitleFull: Identification of Influential Factors and Potentially Hazardous Location of Rear-End Collisions with Hard-Braking Events Data.
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            NameFull: Choe, Cheol-Won
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            NameFull: Kim, Ducknyung
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            NameFull: Kim, Seung-Min
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            NameFull: Park, Ho-Chul
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            – D: 01
              M: 08
              Text: Aug2026
              Type: published
              Y: 2026
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