The fatality and injury risk of light truck impacts with pedestrians in the United States

Lefler, Devon E.; Gabler, Hampton C.

doi:10.1016/s0001-4575(03)00007-1

Cited by 147 publications

(67 citation statements)

References 4 publications

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“…The likelihood Lefler and Gabler [14] used the real-world data from of thorax injuries was considerably higher for LTV the USA to show that 11.5 per cent of pedestrians crashes (37 per cent) than for cars (20 per cent) struck by large SUVs are killed, compared with (p=0.001). The likelihood of abdomen injuries was 4.5 per cent for pedestrians struck by cars.…”

Section: Review Of Empirical Evidence Of Suvmentioning

confidence: 99%

“…Gabler [14] stated that pedestrians are at a severe pedestrian risk from SUVs compared to cars were disadvantage regardless of the mass of the striking 1.97 for traumatic brain injury, 2.0 for thoracic injury, vehicle and suggested that frontal geometry may be and 2.5 for abdominal injuries. They concluded that the controlling factor for pedestrian risk, but they did 'the increased risks to pedestrians of LTVs compared not elaborate on this.…”

Section: Review Of Empirical Evidence Of Suvmentioning

confidence: 99%

“…vehicle registrations [13], while in the USA 40 per Roudsari et al [19] also used the PCDS to analyse cent of new vehicles are either light trucks or SUVs 3146 injuries among 386 pedestrians. There was no [14]. This paper examines the effect of the mass significant difference in mean impact speed between differences and shape differences between cars and LTVs and passenger cars.…”

Section: Introductionmentioning

confidence: 99%

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Pedestrian Risk from Cars and Sport Utility Vehicles - A Comparative Analytical Study

Simms

Wood²

2006

Proceedings of the Institution of Mechanical Engineers, Part D:

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Analysis of real-world crash data from the USA shows that 11.5 per cent of pedestrians struck by large sport utility vehicles (SUVs) are killed, compared with 4.5 per cent of pedestrians struck by passenger cars. The design of the vehicle front-end structure has a substantial influence on injury outcome when pedestrians are struck by vehicles. In the context of the rising population of SUVs, it is important to determine the causes of their increased hazard to pedestrians. In this paper, validated multi-body models are used to show that the shape of SUVs results in higher pedestrian injuries to the mid-body regions compared to passenger cars. Analysis shows that the mass difference between cars and SUVs is not significant for pedestrian injury causation and it is shown that an important effect of the higher front profile of SUVs is that the pedestrian is struck more centrally with respect to the body's centre of gravity, increasing the momentum transfer in the primary impact. A further important effect of the higher bonnet leading edge is that there is a direct impact to the mid-body region, which explains the significant abdomen and other internal injuries reported from real-world SUV/pedestrian impacts. By comparison, head injuries sustained from primary vehicle contact are shown to be similar or slightly lower for SUV/pedestrian impacts compared to car/ pedestrian impacts. However, real-world evidence and the current models suggest that the secondary impact with the ground is more severe in SUV/pedestrian impacts compared to car/ pedestrian impacts. Overall, these results show that the empirical finding that SUVs are more hazardous for pedestrians than passenger cars is primarily a function of the high bumper and bonnet for such vehicles.

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Section: Review Of Empirical Evidence Of Suvmentioning

confidence: 99%

Section: Review Of Empirical Evidence Of Suvmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pedestrian Risk from Cars and Sport Utility Vehicles - A Comparative Analytical Study

Simms

Wood²

2006

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Scholars across the world have done some researches in road accident causation analysis and various data sources, variables, sample sizes, and analytical models, such as aggregated models which include Frequency Analysis [17][18][19] and 2 Test [20,21]. In terms of disaggregated models, as the frequency of road accidents is in a form of nonnegative, discrete, and abnormal distribution and based on experience the frequency of accidents follows Poisson distribution, the Poisson regression model can be applied to analyse the influence of each risk factor on the frequency of accidents [22].…”

Section: Literature Reviewmentioning

confidence: 99%

A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica

Zou

Yue

2017

Journal of Advanced Transportation

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Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents. By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts' knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. Then Netica was used to carry out posterior probability reasoning, the most probable explanation, and inferential analysis. The results showed that the Bayesian network model could effectively explore the complex logical relation in road accidents and express the uncertain relation among related variables. The model not only can quantitatively predict the probability of an accident in certain road traffic condition but also can find the key reasons and the most unfavorable state combination which leads to the occurrence of an accident. The results of the study can provide theoretical support for urban road management authorities to thoroughly analyse the induction factors of road accidents and then establish basis in improving the safety performance of the urban road traffic system.

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“…Relativement à la dimension du réseau routier, nous avons retenu deux composantes. La premiè-re -les débits de trafic -est somme toute classique et souvent associée à l'occurrence des accidents (Mueller et al 1990 ;Roberts et al 1995 ;1995 ;LaScala et al 2004 ;Lefler et Gabler 2004 ;Kweon et Shin 2005 ;Lee et Abdel-Aty 2005 ;zhang et al 2006). Par contre, la seconde composante demeure plus spécifique au cas montréa-lais : nous posons ici l'hypothèse selon laquelle un programme de prévention comme celui des brigadiers scolaires du service de Police de la ville de Montréal 1 peut contribuer à diminuer le risque d'accidents en milieu scolaire.…”

Section: Cadre Conceptuelunclassified

L’environnement autour des écoles a-t-il un impact sur le risque routier impliquant des enfants piétons à Montréal ?

Cloutier¹,

Apparicio²

2008

tem

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The fatality and injury risk of light truck impacts with pedestrians in the United States

Cited by 147 publications

References 4 publications

Pedestrian Risk from Cars and Sport Utility Vehicles - A Comparative Analytical Study

Pedestrian Risk from Cars and Sport Utility Vehicles - A Comparative Analytical Study

A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica

L’environnement autour des écoles a-t-il un impact sur le risque routier impliquant des enfants piétons à Montréal ?

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