The Vehicle Accident Reconstruction using Skid and Yaw Marks

스키드마크 및 요마크를 이용한 차량사고재구성

  • 이승종 (한양대학교 자동차공학과) ;
  • 하정섭 (한양대학교 자동차공학과)
  • Published : 2003.12.01

Abstract

The traffic accident is the prerequisite of the traffic accident reconstruction. In this study, the traffic accident (forward collision) and traffic accident reconstruction (inverse collision) simulations are conducted to improve the quality and accuracy of the traffic accident reconstruction. The vehicle and tire models are used to simulate the trajectories for the post-impact motion of the vehicles after collision. The impact dynamic model applicable to the forward and inverse collision simulations is also provided. The accuracy of impact analysis for the vehicular collision depends on the accuracy of the coefficients of restitution and friction. The neural network is used to estimate these coefficients. The forward and inverse collision simulations for the multi-collisions are conducted. The new method fur the accident reconstruction is proposed to calculate the pre-impact velocities of the vehicles without using the trial and error process which requires the repeated calculations of the initial velocities until the forward collision simulation satisfies with the accident evidences. This method estimates the pre-impact velocities of the vehicles by analyzing the trajectories of the vehicles. The vehicle slides on a road surface not only under the skidding during an emergency braking but also under the steering. A vehicle over steering or cornering with excessive speed loses the traction and leaves tile yaw marks on the road surface. The new critical speed formula based on the vehicle dynamics is proposed to analyze the yaw marks and shows smaller errors than ones of the existing critical speed formula.

Keywords

References

  1. Cannon, J.W., Dependence of a Coefficient of Restitution on Geometry for High Speed Vehicle Collisions, SAE 2001-01-0892
  2. Fricke, L.B., Traffic Accident Reconstruction, Northwestern University Traffic Institute, 1990
  3. Neptune, J.A., Flynn, J.E., Chavez, P.A. and Underwood, H.W., 'peed from Skids: A Modern Approach,' SAE 950354
  4. Han, I. And Park, S-U, 'Inverse Analysis of Pre-and Post-Impact Dynamics for Vehicle Accident Reconstruction,' Vehicle System Dynamics, Vol. 36, No. 6, pp. 413-433, 2001 https://doi.org/10.1076/vesd.36.6.413.3542
  5. Woolley, R.L., The 'IMPACT' Computer Program for Accident Reconstruction, SAE Paper No. 850254, Society of Automotive Engineers, 1985
  6. Steffan, H. and Moser, A., The Collision and Trajectory Models of PC-CRASH, SAE 960886
  7. Cliff, W.E. and Montgomery, D.T., Validation of PC-Crash - A Momentum-Based Accident Reconstruction Program, SAE 960885
  8. Bellion, P., Project Y.A.M. (Yaw Analysis Methodology) Vehicle Testing and Findings - Victoria Police, Accident Investigation Section, SAE 970955, pp. 928-938
  9. Dickerson, C.P., Arndt, S.M., Arndt, M.W. and Mowry, G.A., Evaluation of Vehicle Velocity Predictions Using the Critical Speed Formula, SAE 950137
  10. Brach, R.M., An Analytical Assessment of the Critical Speed Formula, SAE 970957
  11. Kim, M.S., Yang, S.H., Lee, S.H. and Lee, S., 'Lane and Obstacle Recognition using Artificial Neural Network,' J. of the KSPE, Vol. 16, No. 10, pp. 25-34, 1999
  12. Oh, K.H. and Song, C.K., 'Absolute Vehicle Speed Estimation using Neural Network,' J. of the KSPE, Vol. 19, No. 9, pp. 5158-34, 2002
  13. Ishikawa, H., Impact Model for Accident Reconstruction-Normal and Tangential Restitution Coefficients, SAE 930654
  14. Shoemaker, N.E., 'Research Input for Computer Simulation of Automobile Collisions - Staged Collisions,' Vol. 2 & 3, Calspan Report ZQ-6057-V-4 & V-5, Contract DOT-HS-7-01511, Dec. 1978