A mechanistic approach to modeling omnidirectional motorcyclist injury risk

These findings highlight the importance of incorporating biomechanical factors and refined speed metrics into motorcyclist injury risk models. The proposed <i>Effective Collision Speed</i> demonstrated strong predictive capability, offering a more comprehensive approach for assessing injury potential across varied crash configurations.

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Publication Details

Journal
Traffic Injury Prevention
Published
2025-10-01
DOI
https://doi.org/10.1080/15389588.2025.2570829
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

A mechanistic approach to modeling omnidirectional motorcyclist injury risk

Timothy L. McMurry, Angela Schubert, John M. Scanlon, Thomas Unger et al.
Traffic Injury Prevention
Traffic and Road Safety
article

A mechanistic approach to modeling omnidirectional motorcyclist injury risk

Timothy L. McMurry, Angela Schubert, John M. Scanlon, Thomas Unger, Eamon T. Campolettano
article en

Abstract

These findings highlight the importance of incorporating biomechanical factors and refined speed metrics into motorcyclist injury risk models. The proposed <i>Effective Collision Speed</i> demonstrated strong predictive capability, offering a more comprehensive approach for assessing injury potential across varied crash configurations.

Traffic Injury PreventionVol. 26(sup1)
Nomor Research (Germany) (DE), Technische Universität Dresden (DE)
Openalex Percentile: Top 61%
Traffic and Road Safety
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