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PC-Crash is a Windows™ - based accident reconstruction program developed in Graz, Austria by Dr. Hermann Steffan. ...Hermann Steffan. PC-Crash collision analysis results are compared with previously published staged collision data. ...The staged collisions were reconstructed using PC-Crash and the trajectories were compared to actual measurements of the skid marks and rest positions.

The introduction of this model eliminated prior limitations that PC-Crash had for simulating motorcycle motion. Within PC-Crash, a user-defined path can be established for a motorcycle, and the software will generate motion consistent with the user-defined path (within the limits of friction and stability) and calculate the motorcycle lean (roll) generated by following that path at the prescribed speed, braking, or acceleration levels. ...However, the model again did not utilize counter-steering to generate lean, and so it is unlikely that the steering inputs generated by PC-Crash would match the real-world steering inputs. Still, the PC-Crash single-track driver model will yield results that are typically adequate for a crash reconstruction or visualization. ...This paper validates the single-track vehicle driver model available in PC-Crash simulation software. The model is tested, and its limitations are described. The introduction of this model eliminated prior limitations that PC-Crash had for simulating motorcycle motion.

Five collisions were staged in order to evaluate PC-Crash, a simulation program used for investigating motor vehicle collisions. Both vehicles were moving in all of the staged collisions at 1:1 or 2:1 speed ratios. ...Firstly, collision parameters were calculated from measured data, and used as input to the PC-Crash collision model. Secondly, the post-impact vehicle paths and rest positions were used to determine the pre-impact speeds. ...Using the PC-Crash "Optimizer" to reconstruct the five collisions, the error in calculated pre-impact speeds of the ten vehicles ranged from-3.3 to +4.1 km/h.

Next, simulations in PC-Crash were performed, and the results were compared with those obtained in experiments.

PC-Crash simulations of staged collisions require dozens of parameters describing vehicle and impact parameters.

Using the PCM philosophy and including 5 seconds before the accident in the crash analysis combined with the driving behaviours of the vehicles out of PC-Crash, it is possible to analyse, whether or not a sensor system would have been able to recognise the dangerous situation in time to avoid or mitigate the accident.

These predictions were generated by directly integrating the VCH data and by using the VCH data as inputs to PC-Crash simulations. The predicted positions and headings were then compared to the actual position and heading data measured using differential GPS synchronized to the VCH data record.

Furthermore, 183car-to-pedestrian cases, with detailed information regarding accident vehicles, pedestrians and environment, were reconstructed using PC-Crash. A hypothetical autonomous braking system would activate when the pedestrian successfully detected by the sensing system and then new impact speeds will be calculated.

The software packages included in the studies presented in this paper are HVE (SIMON and EDSMAC4), PC-Crash and VCRware. This paper will present the results of the study, conducted using DOE, involving these models.

Knowledge about vehicle rolling resistance is required to calculate speed loss of accident vehicles during portions of their pre-impact and post-impact trajectory when they are not braking or sliding directly sideways. The accuracy of assumed rolling resistance values is most important in accidents with long post-impact roll out distances. Very little hard data are currently available1 and the accident reconstructionist must usually make estimates of drivetrain losses and normal and damaged tire rolling resistance to determine overall vehicle rolling resistance. In the first part of this study, the rolling resistances of various vehicles with different drive configurations are determined, based on accurate measurements made with a 5th wheel. In the second part, sensitivity analyses are done with PC-Crash2, a computer simulation program, to determine what effect the error in assumed rolling resistance has on speed calculations for various types of post-impact trajectories.

Development of crash avoidance systems and active safety systems must not be only based on experimental knowledge. The goal is to provide an efficient answer to still unsolved severe real-world car crashes which occur despite enhanced passive safety devices. This requires to know precisely the pre-crash conditions during about 3 to 10 seconds before impact. The paper describes the multidisciplinary systemic approach leading to the comprehensive methodology used in accident reconstruction in order to determine the best scenario, and to assess initial car speeds, paths and events in the different phases of the accident. This has already been carried out for about 400 car crashes with car occupant injuries (including 6% fatal and 10% severely injured). The necessity of collecting data on the spot of the crash scene is highlighted. Three well-trained investigators are involved.