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


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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    • "(2015), j.ssci.2015.06.005 injury severity (Kim et al., 2007). To indicate the importance of these measures, it was estimated that speed-reducing measures that have been implemented at unsignalized intersections in the Netherlands have prevented some 2.5% of the total number of cyclist fatalities (Schepers and Voorham, 2010; Schepers et al., 2013). "
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    ABSTRACT: Many governments attempt to improve cycling safety to reduce the number of bicycle crashes and encourage cycling. The Netherlands is a world leader in bicycle use and safety. This paper explores how the Netherlands achieved an 80% reduction in the number of cyclists killed (predominantly bicycle–motor vehicle crashes) per billion bicycle kilometres over a thirty year period. Factors found to contribute to this improvement include the establishment of a road hierarchy with large traffic-calmed areas where through traffic is kept out. A heavily used freeway network shifts motor vehicles from streets with high cycling levels. This reduces exposure to high-speed motor vehicles. Separated bicycle paths and intersection treatments decrease the likelihood of bicycle–motor vehicle crashes. The high amount of bicycle use increases safety as a higher bicycle modal share corresponds with a lower share of driving and greater awareness of cyclists among drivers. Low cycling speed was also found to contribute to the high level of cycling safety in the Netherlands.
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    • "A cycle network is only as good as its weakest features and these are often the junctions (ETSC, 1999). In North Carolina, USA, 50.2% of bicycle–motor vehicle accidents occurred at intersections (Kim et al., 2007). Riders' red-light infringement is a type of highly dangerous behavior occurring at intersections. "
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    ABSTRACT: Hazard-based duration models are proposed to investigate riders’ waiting times, violation hazards and associated risk factors.•Most riders are prone to terminate waiting duration and run against the red light over the waiting time elapsed.•Rider type, gender, waiting position, conformity tendency and traffic volume have significant effects on waiting times and violation hazards.•E-bikers are more sensitive to the external risk factors such as other riders’ crossing behavior and crossing traffic volume than cyclists.•The finding of this paper can explain when and why cyclists and e-bikers run against the red light at intersections.
    Accident Analysis & Prevention 01/2015; 74. DOI:10.1016/j.aap.2014.10.014 · 1.87 Impact Factor
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    • "It is therefore difficult to underpin a hypothesis on injury severity. User characteristics such as age are related to injury severity (Kim et al. 2007) and need to be controlled for to conclude whether differences are related due to bicycle type. "
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    ABSTRACT: Use of electrically assisted bicycles with a maximum speed of 25 km/h is rapidly increasing. This growth has been particularly rapid in the Netherlands, yet very little research has been conducted to assess the road safety implications. This case–control study compares the likelihood of crashes for which treatment at an emergency department is needed and injury consequences for electric bicycles to classic bicycles in the Netherlands among users of 16 years and older. Data were gathered through a survey of victims treated at emergency departments. Additionally, a survey of cyclists without any known crash experience, drawn from a panel of the Dutch population acted as a control sample. Logistic regression analysis is used to compare the risk of crashes with electric and classical bicycles requiring treatment at an emergency department. Among the victims treated at an emergency department we compared those being hospitalized to those being send home after the treatment at the emergency department to compare the injury consequences between electric and classical bicycle victims. The results suggest that, after controlling for age, gender and amount of bicycle use, electric bicycle users are more likely to be involved in a crash that requires treatment at an emergency department due to a crash. Crashes with electric bicycles are about equally severe as crashes with classic bicycles. We advise further research to develop policies to minimize the risk and maximize the health benefits for users of electric bicycles.
    Accident Analysis & Prevention 09/2014; 73:174-180. DOI:10.1016/j.aap.2014.09.010 · 1.87 Impact Factor
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