Analysis and application of relationship between post-braking-distance and throw distance in vehicle–pedestrian accident reconstruction

Zou, Tiefang; Yu, Zhi; Cai, Ming; Liu, Jike

doi:10.1016/j.forsciint.2010.09.019

Cited by 25 publications

(16 citation statements)

References 14 publications

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“…Since there was a lack of cases under front impact, the contact angles were classified as left, right, and back. The car impact speed was calculated from the braking distance or the pedestrian throwing distance [32], or it was obtained from videos [33] or an event data recorder (EDR) [34]. Cases were grouped into three categories according to impact speed: 25–39, 40–55, and ≥55 km/h.…”

Section: Methodsmentioning

confidence: 99%

Exploration of Pedestrian Head Injuries—Collision Parameter Relationships through a Combination of Retrospective Analysis and Finite Element Method

Liu

Qiu

et al. 2016

IJERPH

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There are a very limited number of reports concerning the relationship between pedestrian head injuries and collision parameters through a combination of statistical analysis methods and finite element method (FEM). This study aims to explore the characteristics of pedestrian head injuries in car–pedestrian collisions at different parameters by using the two means above. A retrospective analysis of pedestrian head injuries was performed based on detailed investigation data of 61 car–pedestrian collision cases. The head damage assessment parameters (head injury criterion (HIC), peak stress on the skull, maximal principal strain for the brain) in car–pedestrian simulation experiments with four contact angles and three impact velocities were obtained by FEM. The characteristics of the pedestrian head injuries were discussed by comparing and analyzing the statistical analysis results and finite element analysis results. The statistical analysis results demonstrated a significant difference in skull fractures, contusion and laceration of brain and head injuries on the abbreviated injury scale (AIS)3+ was found at different velocities (p < 0.05) and angles (p < 0.05). The simulation results showed that, in pedestrian head-to-hood impacts, the values of head damage assessment parameters increased with impact velocities. At the same velocity, these values from the impact on the pedestrian’s back were successively greater than on the front or the side. Furthermore, head injury reconstruction and prediction results of two selected cases were consistent with the real injuries. Overall, it was further spelled out that, for shorter stature pedestrians, increased head impact velocity results in greater head injury severity in car–pedestrian collision, especially in pedestrian head-to-hood impacts. Under a back impact, the head has also been found to be at greater damage risk for shorter stature pedestrians, which may have implications on automotive design and pedestrian protection research if prevention and treatment of these injuries is to be prioritized over head injuries under a front or side impact.

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Section: Methodsmentioning

confidence: 99%

Exploration of Pedestrian Head Injuries—Collision Parameter Relationships through a Combination of Retrospective Analysis and Finite Element Method

Liu

Qiu

et al. 2016

IJERPH

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“…To obtain an analytical model for calculating S p according to v , as discussed in references and , four hypotheses are formed as follows:…”

Section: Methodsmentioning

confidence: 99%

“…References and focus on wrap collisions, in which the vehicle is assumed to move along a slope road. Figure shows a sketch of the wrap collision sequence and indicates various variables in a vehicle–pedestrian accident, such as the impact speed v , the flight‐phase distance R , the launched angle of the pedestrian θ , the launched velocity of the pedestrian v p 0 , the height of the pedestrian center of gravity at launch h , the slide distance of the pedestrian S , the slide distance of the vehicle S v , the road slope α , and the throw distance S p = R + S .…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Due to its severity, many efforts have focused on its reconstruction to identify responsibility and develop mitigating measures. For example, methods based on the postbraking distance (the postbraking distance refers to the distance that a vehicle will travel from the impact position to the position at which it comes to a complete stop ), the throw distance , the vehicle damage and/or the pedestrian injury , and all traces (the braking distance, the throw distance, the vehicle damage, and the pedestrian injury). Methods that are based on all traces are generally based on simulation software , for example, Pc‐Crash and Madymo, and can be considered to be simulation methods.…”

mentioning

confidence: 99%

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Two Simple Formulas for Evaluating the Lower Bound of the Impact Velocity in Vehicle–pedestrian Accidents

Zou

Yong-gang

Yin

2016

Journal of Forensic Sciences

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Formulas for evaluating the lower bound of the impact velocity are valuable in vehicle-pedestrian accident reconstruction. The theory of classical mechanics and four hypotheses were employed to derive formulas; the research results and simulation/accident tests were employed to validate their feasibility. Then, two simple formulas were developed according to the distance between the rest positions of the vehicle and the pedestrian and the flight-phase distance. The results showed that the evaluated results by the two proposed formulas are inferior to the existing results. The influence of a roadside step on the impact velocity, which decreased with an increase in the flight-phase distance and a reduction in the road slope, was evaluated. Based on a real accident, the study concludes that the lower bound can be easily obtained with the proposed formulas, which can be used to determine the evaluated impact velocity during simulations.

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“…The system limits maximum velocity to 200 km/h. In this case, the safety relative distance between preceding vehicle and following vehicle is approximately 110 m [19], [20]. Thus, considering the safety distance and many type of vehicle, the maximum relative distance is limited to approximately 200 m. If the relative heading angle is over 90 degrees, system terminates the driving.…”

Section: Driving Termination Algorithmmentioning

confidence: 99%

Multiple Vehicles Semi-Self-driving System Using GNSS Coordinate Tracking under Relative Position with Correction Algorithm

Lee¹,

Suzuki²,

Kitajima³

et al. 2017

ijacsa

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Abstract-This paper describes a simple and low-cost semiself-driving system which is constructed without cameras or image processing. In addition, a position correction method is presented by using a vehicle dynamics. Conventionally, selfdriving vehicle is operated by various expensive environmental recognition sensors. It results in rise in prices of the vehicle, and also the complicated system with various sensors tends to be a high possibility of malfunction. Therefore, we propose the semi-self-driving system with a single type of global navigation satellite system (GNSS) receiver and a digital compass, which is based on a concept of a preceding vehicle controlled by a human manually and following vehicles which track to the preceding vehicle automatically. Each vehicle corrects coordinate using current velocity and heading angle from sensors. Several experimental and simulation results using our developed smallscale vehicles demonstrate the validity of the proposed system and correction method.

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Analysis and application of relationship between post-braking-distance and throw distance in vehicle–pedestrian accident reconstruction

Cited by 25 publications

References 14 publications

Exploration of Pedestrian Head Injuries—Collision Parameter Relationships through a Combination of Retrospective Analysis and Finite Element Method

Exploration of Pedestrian Head Injuries—Collision Parameter Relationships through a Combination of Retrospective Analysis and Finite Element Method

Two Simple Formulas for Evaluating the Lower Bound of the Impact Velocity in Vehicle–pedestrian Accidents

Multiple Vehicles Semi-Self-driving System Using GNSS Coordinate Tracking under Relative Position with Correction Algorithm

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