Using random forest to test if two-wheeler experience affects driver behavior when interacting with two-wheelers

, , , & (2019) Using random forest to test if two-wheeler experience affects driver behavior when interacting with two-wheelers. In The Australasian Road Safety Conference 2019, 2019-09-25 - 2019-09-27, Adelaide, SA, Australia. (Unpublished)

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Drivers are often at-fault in collisions with powered and unpowered Two-Wheelers (TW). In this paper, we propose a framework based on the random forest algorithm to investigate whether TW experience influences driver interactions with TWs. Sixty-nine drivers completed a 10-minute driving simulator session which included five interactions based on common car-TW crash types. The TWs were initially positioned in front of, or at right angles to, the driven vehicle. The proposed framework detected a statistically significant difference between drivers with TW experience and those without despite the small sample size.

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ID Code: 203752
Item Type: Contribution to conference (Abstract)
Refereed: Yes
ORCID iD:
Elhenawy, Mohammedorcid.org/0000-0003-2634-4576
Larue, Gregoireorcid.org/0000-0001-8564-9084
Rakotonirainy, Andryorcid.org/0000-0002-2144-4909
Haworth, Narelleorcid.org/0000-0003-2514-787X
Measurements or Duration: 3 pages
Pure ID: 67543835
Divisions: Past > QUT Faculties & Divisions > Faculty of Health
Past > Institutes > Institute of Health and Biomedical Innovation
Current > Research Centres > CARRS-Q Centre for Future Mobility
Copyright Owner: Consult author(s) regarding copyright matters
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Deposited On: 02 Sep 2020 08:49
Last Modified: 09 Nov 2026 04:11