Impact severity assessment in vehicle accidents

Vangi, Dario

doi:10.1080/13588265.2014.921974

Cited by 12 publications

(18 citation statements)

References 11 publications

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“…), that is, before the accident outcome is known. In such approach, the following relation 16 can be given for the subject vehicle (e.g. vehicle 1)…”

Section: Methodsmentioning

confidence: 99%

“…In a prospective approach, CMI can be expressed knowing the accident outcome, that is, the velocity change experienced by the subject vehicle per unit closing velocity as follows 16,19…”

Section: Methodsmentioning

confidence: 99%

“…14,15 They are related to the value of the kinetic energy lost in vehicles deformation and affect the Δ V resulting from the crash. 16…”

Section: Introductionmentioning

confidence: 99%

“…with which part and at which angle the vehicles impact) that can be expressed by means of the crash momentum index (CMI). 16,19 In fact, at equal closing velocity, different impact configurations determine a different Δ V of the vehicles; the structural behaviour (passive safety) can also change based on the deformed vehicle portion. To take into account this variable behaviour of the vehicle, distinct IR-ΔV curves are often considered for front, rear and side impacts, distinguishing the latter ones in near-side and far-side.…”

Section: Introductionmentioning

confidence: 99%

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Crash momentum index and closing velocity as crash severity index

Vangi

Gulino

Fiorentino

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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The velocity change Δ V of a vehicle subject to a collision, widely recognized as an efficient crash severity indicator, is a typical ‘a posteriori’ parameter, not generally known until the crash phase has been reconstructed. Δ V is the result of a combination of factors, regarding the impact velocities of the colliding vehicles and the geometry of the impact (as eccentricity, etc.): for this reason, its value alone gives no clear indications on the actions which can be undertaken to reduce crash severity. This feature is particularly critical in some application fields, for example, in case of advanced driver assistance systems assessment in different accident scenarios. This work proposes the disaggregation of Δ V into two different ‘a priori’ parameters to assess crash severity of an impact before its occurrence: the crash momentum index, representing the impact configuration, and the closing velocity projected along the principal direction of force ( Vr_pdof), as an index of the kinetic energy exchanged between the two vehicles. It is preliminarily shown how the proposed parameters can be calculated using established procedures – as momentum-based analysis – in a predictive (‘a priori’) approach. It is also evidenced how crash momentum index, Vr_pdof and the velocity change Δ V are in relation. To illustrate the procedure by means of examples, binary logistic regression on accident data is applied to correlate crash momentum index and Δ V to injury risk at Maximum Abbreviated Injury Scale level higher than 2. The use of crash momentum index as an additional severity index allows an improved correlation with injury risk, for the dataset used, in case of front and near side impacts. The use of the plane Vr_pdof– crash momentum index, on which curves at constant injury risk are drawn, provides clear indications on the possible strategies to reduce injury risk, as shown by generic examples to which the predictive procedure is applied.

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“…), that is, before the accident outcome is known. In such approach, the following relation 16 can be given for the subject vehicle (e.g. vehicle 1)…”

Section: Methodsmentioning

confidence: 99%

“…In a prospective approach, CMI can be expressed knowing the accident outcome, that is, the velocity change experienced by the subject vehicle per unit closing velocity as follows 16,19…”

Section: Methodsmentioning

confidence: 99%

“…14,15 They are related to the value of the kinetic energy lost in vehicles deformation and affect the Δ V resulting from the crash. 16…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Crash momentum index and closing velocity as crash severity index

Vangi

Gulino

Fiorentino

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

View full text Add to dashboard Cite

show abstract

“…Many different numerical tools are currently available for analyzing dangerous traffic situations [22]. One of the fastest are calculations using analytical formulae that take into account, among other things, the velocity, weight and stiffness of vehicles [23][24][25]. They allow many scenarios to be analyzed in a very short time and, when supplemented with a reliable vehicle database, make it possible to assess a real accident.…”

Section: Introductionmentioning

confidence: 99%

Impact of Disabled Driver’s Mass Center Location on Biomechanical Parameters during Crash

Sybilski

Małachowski

2021

Applied Sciences

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Adapting a car for a disable person involves adding additional equipment to compensate for the driver’s disability. During this process, the change in the driver’s position and kinematics and their impact on safety levels during crash is not considered. There is also a lack of studies in the literature on this problem. This paper describes a methodology for conducting a study of the behavior of a disabled driver during a crash using the finite element method, based on an explicit time integration method. A validated car model and a commercial dummy model were used. The results show that the use of a handle on the steering wheel and a hand control unit causes dangerous lateral displacements relative to the seat. Amputation of the left leg or right arm causes significant shoulder rotations, amputation of the left leg causes increased thoracic loads. Amputation or additional equipment have no significant impact on head injuries.

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Vehicle crash mitigation strategy in unavoidable collision scenarios: focusing on motion planning by considering a generalized crash severity model

Zhang

Xiao

et al. 2022

J Braz. Soc. Mech. Sci. Eng.

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Driving strategy in dynamic environment is crucial to the automated vehicle safety. In extremely emergency scenarios with unavoidable collisions, especially those with complex impact patterns, the potential crash risk should be well considered. This paper proposes a crash mitigation algorithm for unavoidable collisions, which directly embeds a generalized crash severity index model to vehicle-to-vehicle collisions of multiple impact patterns. The idea is that during the short time before a collision, the vehicle will actively adapt its position and poses to minimize the potential crash severity level after the collision. To this end, the generalized crash severity index (CSI) model is introduced to estimate the potential crash severity of all sample paths, from which a crash-severityoptimal trajectory is obtained. To improve the inferring time efficiency of the planning module, a neural network is constructed and deployed to approximate the nonlinear severity model. The proposed algorithm is first validated through simulations of unavoidable collision scenarios, Vehicle Crash Mitigation Considering CSI model including entry ramp merging, intersection crossing and downhill/uphill crossing. Then for the intersection crossing scenario, the algorithm is deployed to a real car and validated through digital-twin experiments. Results show that by combining the braking and steering interventions for better crash severity reduction, the proposed strategy can achieve better mitigation effects than commonly-used collision-avoidance strategies. This reveals that a new mindset of comprehensive safety strategy should not focus only on collision avoidance, but also the last resort of crash mitigation if collision is unavoidable. Our work may contribute as a promising solution to the safety problem in emergency scenarios.

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Impact severity assessment in vehicle accidents

Cited by 12 publications

References 11 publications

Crash momentum index and closing velocity as crash severity index

Crash momentum index and closing velocity as crash severity index

Impact of Disabled Driver’s Mass Center Location on Biomechanical Parameters during Crash

Vehicle crash mitigation strategy in unavoidable collision scenarios: focusing on motion planning by considering a generalized crash severity model

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