Errors and violations in relation to motorcyclists’ crash risk

Elliott, Mark A.; Baughan, C J; Sexton, B

doi:10.1016/j.aap.2006.08.012

Cited by 220 publications

(215 citation statements)

References 19 publications

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“…Paying attention and obeying traffic laws are motorcyclist-related obligations and, according to the obtained results, the non-fulfillment of the first predicts the non-fulfillment of the second. These results are in line with those obtained in previous research as far as the relationship between distraction and accident rate is concerned (RANDOM, 2005;Cheng and Ng, 2010;Elliott et al, 2007), given that distraction increases the offending behavior of the motorcyclist involved in an accident.…”

Section: Resultssupporting

confidence: 92%

“…Lin and Kraus, 2009;Moskal et al, 2012;NHTSA, 2007;Savolainen and Mannering, 2007;Shankar, 2003;Shankar and Mannering, 1996), distraction Cheng and Ng, 2010;Elliott et al, 2007;RANDOM, 2005) and fatigue (Peden et al, 2004;Philip et al, 2003;Sanchez, 2001). …”

Section: Motorcyclist Characteristicsmentioning

confidence: 99%

“…Motorcycle drivers specifically do have a greater risk of being victims (fatalities or injuries) in a traffic accident compared with any other vehicle user (Elliott et al, 2007;Keall and Newstead, 2012). The risk of having an accident to which they are exposed is several times higher than the other drivers' (Horswill and Helman, 2003) and, compared with passenger car drivers, the risk of fatality is seven times higher for motorcyclists (ONISR, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Modeling offenses among motorcyclists involved in crashes in Spain

Pérez-Fuster

Rodrigo

Ballestar

et al. 2013

Accident Analysis & Prevention

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In relative terms, Spanish motorcyclists are more likely to be involved in crashes than other drivers and this tendency is constantly increasing. The objective of this study is to identify the factors that are related to being an offender in motorcycle accidents. A binary logit model is used to differentiate between offender and non-offender motorcyclists. A motorcyclist was considered to be offender when s/he had committed at least one traffic offense at the moment previous to the crash. The analysis is based that inexperienced, older females, not using helmets, absent-minded and non-fatigued riders are more likely to be offenders. Moreover, riding during the night, on weekends, for leisure purposes and along roads in perfect condition, mainly on curves, predict offenses among motorcyclists. The findings of this study are expected to be useful in developing traffic policy decisions in order to improve motorcyclist safety.

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Section: Resultssupporting

confidence: 92%

Section: Motorcyclist Characteristicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling offenses among motorcyclists involved in crashes in Spain

Pérez-Fuster

Rodrigo

Ballestar

et al. 2013

Accident Analysis & Prevention

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“…Cronbach's alpha was calculated for the five factors that were identified by Elliot et al (2007). The alphas, and the mean scores across groups, are presented in Table 3.…”

Section: <Table 2 Here>mentioning

confidence: 99%

“…This is a 43 item questionnaire that is reported to produce a five-factor structure, including traffic errors, speed violations, engagement in stunts, use of safety equipment, and control errors (Elliot et al, 2007).…”

Section: Designmentioning

confidence: 99%

The role of experience and advanced training on performance in a motorcycle simulator

Crundall¹,

Stedmon²,

Crundall³

et al. 2014

Accident Analysis & Prevention

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Motorcyclists are over-represented in collision statistics. While many collisions may be the direct fault of another road user, a considerable number of fatalities and injuries are due to the actions of the rider. While increased riding experience may improve skills, advanced training courses may be required to evoke the safest riding behaviours. The current research assessed the impact of experience and advanced training on rider behaviour using a motorcycle simulator. Novice riders, experienced riders and riders with advanced training traversed a virtual world through varying speed limits and roadways of different curvature. Speed and lane position were monitored. In a comparison of 60 mph and 40 mph zones, advanced riders rode more slowly in the 40 mph zones, and had greater variation in lane position than the other two groups. In the 60 mph zones, both advanced and experienced riders had greater lane variation than novices. Across the whole ride, novices tended to position themselves closer to the kerb. In a second analysis across four classifications of curvature (straight, slight, medium, tight) advanced and experienced riders varied their lateral position more so than novices, though advanced riders had greater variation in lane position than even experienced riders in some conditions. The results suggest that experience and advanced training lead to changes in behaviour compared to novice riders which can be interpreted as having a potentially positive impact on road safety.3

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A multiple correspondence analysis of at‐fault motorcycle‐involved crashes in Alabama

Jalayer

Zhou

2016

J of Advced Transportation

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According to the U.S. National Highway Traffic Safety Administration, in 2012, more than 4950 motorcyclists were killed in traffic accidents. Compared to passenger car occupants, mile for mile, motorcyclists are more than 26 times more at risk to dying in crashes. Due to the high fatality rate associated with motorcycle crashes, factors contributing to this type of crash must be identified in order to implement effective safety countermeasures. Given that the available datasets are large and complex, identifying the key factors contributing to crashes is a challenging task. Using multiple correspondence analysis, as an exploratory data analysis technique to determine the dataset structure, we identified the roadway/environmental, motorcycle, and motorcyclist-related variables influencing at-fault motorcycle-involved crashes. This study used the latest available dataset (2009 to 2013) from the Critical Analysis Reporting Environment database to study motorcycle crashes in the state of Alabama. The most significant contributors to the frequency and severity of at-fault motorcycle-involved crashes were found to be light conditions, time of day, driver condition, and weather conditions.

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Errors and violations in relation to motorcyclists’ crash risk

Cited by 220 publications

References 19 publications

Modeling offenses among motorcyclists involved in crashes in Spain

Modeling offenses among motorcyclists involved in crashes in Spain

The role of experience and advanced training on performance in a motorcycle simulator

A multiple correspondence analysis of at‐fault motorcycle‐involved crashes in Alabama

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