Advanced SearchSearch Tips
Prediction of Assistance Force for Opening/Closing of Automobile Door Using Support Vector Machine
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Prediction of Assistance Force for Opening/Closing of Automobile Door Using Support Vector Machine
Yang, Hac-Jin; Shin, Hyun-Chan; Kim, Seong-Kun;
  PDF(new window)
We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user`s force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.
Artificial Neural Network(ANN);Assistance Force;Mechanism;OEM Door;Support Vector Machine(SVM);
 Cited by
S. H. Yoon, S. W. Moon, K. I. Seo and J. H. Hwang, "Development of Smart Cruise Control System with the Consideration of Driver's Tendency", KSME IT, Spring Conference, pp.89-90, 2014.

Y. W. Yun, G. J. Park and T. K. Kim, "Effectiveness of Active Hood and Pedestrian Airbag Based on Real Behicle Impact Test", Transactions of KSAE, Vol.22, No.1, pp.36-45, 2014.

J. K. Lee, "Development Trends of Smart Safety Vehicle", Auto Journal, Vol.33, No.5, pp.38-44, 2011.

C. G. Oh, J. H. Choi and B. H. Jung, "Mechanism Study for the Invisible Rail Sliding Door using 6-Bar Linkage", KSAE, Fall Conference, pp. 1722-1727, 2012.

S. J. Chai, I. D. Hwang, S. H. Heo and S. C. Choi, "A Development of the Body with B Pillarless Sliding Door Type", KSAE, Fall Conference, pp. 1874-1882, 2011.

K. G. Sung, M. K. Park and B. S. Lee, "Design of Power-Assist Smart Door System for Passenger Vehicle", Journal of institute of control, robotics and systems, Vol.16, No.6, pp.532-538, 2010. crossref(new window)

B. S. Lee, M. K. Park and K. G. Sung, "Velocity Control and Collision Detection by Feedback Linearization for an Power-assisted Automotive Swing Door", Transaction of KSAE, Vol.21, No.5, pp.40-46, 2013. DOI: crossref(new window)

H. J. Yang, S. K. Kim, "Design of Wafer Handling Robot Using Kernel Regression and Neural Network", Proceeding of KSME Spring Conference, pp.67-68, 2010.

K. H. Jang, T. K. Yoo, J. Y. Choi, K. C. Nam, J. L. Choi, M. K. Kwon, and D. W. Kim, "Comparison of survival predictions for rats with hemorrhagic shocks using an artificial neural network and support vector machine," Journal of the institute of electronics and information engineers, Vol.34, No.1, pp.1148-1151, 2011. DOI: crossref(new window)

W. K Youn and J. Kim, "Mechanomyo- graphy(MMG) based Elbow Flexion Force Prediction for Human-Machine Interaction", Journal of Mechanical Science and Technology, Vol.9, pp.2752-2756, 2009.

K. K. Seo, "A Comparison Study on Back-Propagation Neural Network and Support Vector Machines for thr Image Classification Problems", Journal of the KAIS, Vol. 9, No.6, pp.1889-1893, 2008.

H. J. Yang, S. K. Kim and J. K. Cho, "Design and Performance Test of Large-Area Susceptor for the Improvement of Temperature Uniformity", Journal of the KAIS, Vol. 16, No. 6 pp.3714-3721, 2015. DOI: crossref(new window)

Alex J. Smola and Bernhard Scholkopf, "A tutorial on support vector regression", Statistics and Computing, Vol.14, No.3, pp.199-222, 2004. DOI: crossref(new window)

H. J Yang, S. K. Kim and K. H Choi, "A Study of the Feature Classification and the Predictive Model of Main Feed-Water Flow for Turbine Cycle", Journal of Energy Engineering, Vol.23, No.4, pp.263-271, 2014. DOI: crossref(new window)

C. J. C. Burges, "A Tutorial on Support Vector Machines for Pattern Recognition", Data Mining and Knowledge Discovery, Vol.2, pp.121-167, 1998. DOI: crossref(new window)

B. Scholkopf, K. Sung, C. Burges, F. Girosi, P. Niyogi, T. Poggio, and V. Vapnik, "Comparing support vector machines with Gaussian kernels to radial basis function classifiers", IEEE Transactions on Signal Processing, Vol.45, No.11, pp.2758-2765, 1997. DOI: crossref(new window)