Investigating the Impact of Truck Classes on Non-Truck Crash Severity Using Correlated Random-Parameter Binary Logit Model
ID:1885 View Protection:ATTENDEE Updated Time:2021-12-03 14:41:54 Hits:218 Poster Presentation

Start Time:2021-12-17 08:37(Asia/Shanghai)

Duration:1min

Session:P2 Poster2021 » P2T4Track 4 Transportation Behavior, Safety and Security

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Abstract
This study aims to investigate the role of the of truck volumes of various classes on the severity of non-truck crashes, with which the correlations between space-time-varying heterogeneities are considered. Fixed-, uncorrelated and correlated random-parameter binary logit models are established, based on crash and traffic data of five freeway segments in Shandong of China during 2016 to 2019. In total, 4,008 crashes on 5 freeways are extracted from the database and stratified into space-time panels. Results indicate that the proposed correlated random-parameter model is the optimal model among the three. Correlation in the heterogeneous effects between super-large truck volume and average speed is significant. The increase in mid-sized truck volume is associated with the increase in the crash severity of non-truck involved crashes, which gets weakened along the increasing total traffic volume.
Keywords
CICTP
Speaker
Fanyu Meng
Southern University of Science and Technology

Submission Author
Fanyu Meng Southern University of Science and Technology
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  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

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Chinese Overseas Transportation Association
Chang'an University
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