CONTACT US: Contact info
|
Citation |
Ding C, Rizzi M, Strandroth J, Sander U, Lubbe N. Accid. Anal. Prev. 2019; 123: 374-386. |
|
Affiliation |
Autoliv Research, Vårgårda, Sweden. |
|
Copyright |
(Copyright © 2019, Elsevier Publishing) |
|
DOI |
|
PMID |
30597331 |
|
Abstract |
The Vision Zero approach advocates for a road transport system designed with human injury tolerance and human fallibility as its basis. While biomechanical limits and the relationship between speed and injury outcome has been extensively investigated for car occupants and pedestrians, research analyzing this relationship for motorcyclists remains limited. The aim of this study was to address this issue by developing multivariate injury risk models for motorcyclists that estimate the relationship between speed and injury severity. For that purpose, motorcycle injury crashes from the German In-Depth Accident Study (GIDAS) database for the period 1999-2017 (n = 1037) were extracted. Different models were tested using logistic regression and backwards elimination of non-significant variables. The best fitting model in the current study included relative speed, type of crash opponent, impact location on the motorcycle and impact mechanism of the rider during the crash. A strong and significant relationship between relative speed and injury severity in motorcycle crashes was demonstrated. At 70 km/h, the risk for at least serious injuries in collisions with wide objects, crash barriers and narrow objects was 20%, 51%, and 64%, respectively. Further, it was found that head-on collisions between motorcycles and passenger cars, with both vehicles traveling at 60 km/h (a relative speed at 120 km/h), present 55% risk of at least serious injury to the motorcycle rider. More research is needed to fully understand the boundary conditions needed to design a safe road transport system for motorcyclists. However, this study provides important insights into the relationship between speed and injury severity for riders in various crash situations. The results may be useful in the discussion of appropriate speed limits and in determining the benefits of countermeasures which aim to reduce crash speed. Language: en |
|
Keywords |
GIDAS; Injury; Logistic regression; Motorcycle; Risk model; Speed |