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The accuracy of collision severity data recorded by event data recorders (EDRs) has been previously measured primarily using barrier impact data from compliance tests and experimental low-speed impacts. There has been less study of the accuracy of EDR-based collision severity data in real-world, vehicle-to-vehicle collisions. Here we used 189 real-world front-into-rear collisions from the Crash Investigating Sampling System (CISS) database where the EDR from both vehicles recorded a severity to examine the accuracy of the EDR-reported speed changes. We calculated relative error between the EDR-reported speed change of each vehicle and a speed change predicted for that same vehicle using the EDR-reported speed change of the other vehicle and conservation of momentum. We also examined the effect of vehicle-type, mass ratio, and pre-impact braking on the relative error in the speed changes.

Our goal was to evaluate whether modifications to the force-displacement curves derived from a high-speed NHTSA frontal barrier test could be used to improve predictions of the equivalent barrier speed of a low-speed crash involving the same vehicle. Using an earlier iteration of the technique described here, Hunter et al. [2] showed that the F-D curves from higher-speed tests over-predicted the EBS of lower-speed tests by 21±17%. After modifying the earlier technique to account for powertrain stack-up and barrier force attenuation prior to reaching peak dynamic crush, the technique evaluated here reduced this error to 1% with a standard deviation that varied between ±9% and ±13% depending on which engine accelerometers were chosen for the adjustment. These findings suggest that the method and modifications proposed here can be used to reconstruct car crashes provided that there is a relationship between dynamic crush and residual crush.

The objectives of this study were to use Finite Element (FE) simulations to predict the crush profile resulting from frontal pole impacts and to compare the results of the FE simulations to existing reconstruction methods. A 2001 Ford Taurus FE model created by the National Crash Analysis Center (NCAC) was used to simulate four pole impact tests performed by the Insurance Institute of Highway Safety (IIHS) involving the same generation of Ford Taurus. The FE crush profiles show good correlation to the physical tests. The maximum crush was predicted within ±3% for three of the tests and was under predicted by 7% in the fourth test. The same FE model was then used to simulate 22 more pole impacts to study how impact speed and lateral pole offset from the centerline affected maximum crush. At impact speeds of 32 km/h, the maximum crush did not vary by more than 4 cm for different pole locations ±500 mm from the vehicle centerline.

The objective of this study was to assess the accuracy of using high-speed frontal barrier crash tests to predict the impact speed, i.e. equivalent barrier speed (EBS), of a lower-speed frontal barrier crash. Force-displacement (F-D) curves were produced by synchronizing the load cell barrier (LCB) data with the accelerometer data. Our analysis revealed that the F-D curves, including the rebound phase, for the same vehicle model at the same impact speed were generally similar. The test vehicle crush at the time of barrier separation, determined from the F-D curves, was on average 17±16% (N = 150) greater than the reported maximum hand-measured residual crush to the bumper cover. The EBS calculated from the F-D curves was on average 4±4% (N=158) greater than the reported EBS, indicating that using F-D curves derived from LCB data is a reliable method for calculating vehicle approach energy in a crash test.

CRASH3 techniques are often used to reconstruct aligned offset vehicle impacts. The goal of this study was to evaluate the accuracy of the CRASH3 technique using a series of aligned staged collision with varying degrees of overlap. Five front-to-rear vehicle impacts using the same vehicle model were staged using 25, 33, 50, 75 and 100% overlap. Impact kinematics were measured using overhead high speed video. The CRASH3 coefficients and methods developed previously (SAE 2010-01-0069) were used to reconstruct the impact speed and speed changes of both vehicles based on the residual crush. Overall, the CRASH3 analysis yielded good results for the 33 to 100% overlap collisions: predicted speed changes were within 29% of the measured speed change and predicted impact speeds were within 16% of the measured impact speed.

Numerical parameters describing suspension stiffness and damping are required for 3D simulation of vehicle trajectories, but may not be available. This paper outlines a simple, portable method of measuring these properties with a coefficient of variation of 5% on stiffness. 24 of 26 vehicles tested were significantly stiffer in roll than pitch, complicating analyses with models that don't include anti-roll. Suspension parameters did not correlate with static wheel load distribution, and damping coefficient did not correlate with natural frequency. Computer simulations of the speed required to initiate rollover in an S-curve were highly sensitive to the suspension parameters used. When pre-impact tire marks and rollover distance were considered, the simulations became almost insensitive to suspension parameters.

Quantifying the energy associated with vehicle damage is the basis of common methods used to reconstruct car crashes. This study sought to characterize the relationship between crush and energy for the front and rear surfaces of a passenger car. Nine stationary barrier crash tests and one aligned car-to-car test were conducted using several cars of the same model with impact speeds ranging from 4.3 to 15.2 m/s generating as much as 0.47 m of crush. The results revealed a linear speed-crush relationship for front and rear car surfaces and a restitution coefficient that decreased from a maximum of 0.33 at low speed to a relatively constant value of 0.15 for crush levels above 0.2 m. Crush coefficients derived from the crash tests were compared to the coefficients from three other sources: i) default values from the CRASH3 computer program, ii) values from a published database and iii) values derived from an assumed damage threshold value and an NHTSA high-speed crash test.