Bicyclist injury severities in bicycle-motor vehicle accidents.

Washington University in St. Louis, Department of Civil Engineering, Campus Box 1130, One Brookings Drive, St. Louis, MO 63130-4899, USA.
Accident Analysis & Prevention (Impact Factor: 1.87). 04/2007; 39(2):238-51. DOI: 10.1016/j.aap.2006.07.002
Source: PubMed

ABSTRACT This research explores the factors contributing to the injury severity of bicyclists in bicycle-motor vehicle accidents using a multinomial logit model. The model predicts the probability of four injury severity outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. The analysis is based on police-reported accident data between 1997 and 2002 from North Carolina, USA. The results show several factors which more than double the probability of a bicyclist suffering a fatal injury in an accident, all other things being kept constant. Notably, inclement weather, darkness with no streetlights, a.m. peak (06:00 a.m. to 09:59 a.m.), head-on collision, speeding-involved, vehicle speeds above 48.3 km/h (30 mph), truck involved, intoxicated driver, bicyclist age 55 or over, and intoxicated bicyclist. The largest effect is caused when estimated vehicle speed prior to impact is greater than 80.5 km/h (50 mph), where the probability of fatal injury increases more than 16-fold. Speed also shows a threshold effect at 32.2 km/h (20 mph), which supports the commonly used 30km/h speed limit in residential neighborhoods. The results also imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault.

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The results show that more type I crashes occur at intersections with two-way bicycle tracks, well-marked, and reddish coloured bicycle crossings. Type I crashes are negatively related to the presence of raised bicycle crossings (e.g. on a speed hump) and other speed reducing measures. The accident probability is also decreased at intersections where the cycle track approaches are deflected between 2 and 5m away from the main carriageway. No significant relationships are found between type II crashes and design factors such as the presence of a raised median. Chapter 5 focuses on research question 3b: What single-bicycle crash types can be distinguished and can these be related to infrastructure?A literature search showed that only a few studies addressed single-bicycle crashes (i.e. a fall or obstacle collision). These studies and theories were used to develop a draft categorization of single-bicycle crash types. 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Question 3c is about the role of visibility of infrastructure in single-bicycle crashes: What do cyclists need to see to avoid single-bicycle crashes?This question is addressed in Chapter 6. To study the role of visual characteristics of the infrastructure, such as pavement markings, in single-bicycle crashes, a study in two steps was conducted. In Study 1, a questionnaire study was conducted among bicycle crash victims. Logistic regression was used to study the relationship between the crashes and age, light condition, alcohol use, gaze direction and familiarity with the crash scene. In Study 2, the image degrading and edge detection method (IDED-method) was used to investigate the visual characteristics of 21 of the crash scenes. The results of the studies indicate that crashes, in which the cyclist collided with a bollard or road narrowing or rode off the road, were related to the visual characteristics of bicycle facilities. 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The analyses were conducted using data of all Dutch municipalities with more than 50,000 inhabitants. Negative binomial regression was used to analyse the effect on the number of police-reported cyclist deaths and in-patients in bicycle-motor vehicle crashes. A mediation model was tested, with Structural Equation Modelling hypothesizing that unbundling corresponds positively with the cycling modal share via the length of car trips divided by those by bicycle. The results of this study suggest that unbundling improves cycling safety, and increases the share of cycling in the modal split (as a result of improved competitiveness of cycling in terms of trip length). Chapter 8 discussed the main findings of the research conducted throughout the thesis and considered the implications. It can be concluded that cycling safety is affected by the road design. 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    12/2013, Degree: PhD, Supervisor: Prof. ir. F.C.M. Wegman


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