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http://dx.doi.org/10.15207/JKCS.2017.8.9.285

A RLS-based Convergent Algorithm for Driving Characteristic Classification for Personalized Autonomous Driving  

Oh, Kwang-Seok (Department of Mechanical Engineering, Hankyong National University)
Publication Information
Journal of the Korea Convergence Society / v.8, no.9, 2017 , pp. 285-292 More about this Journal
Abstract
This paper describes a recursive least-squares based convergent algorithm for driving characteristic classification for personalized autonomous driving. Recently, various researches on autonomous driving technology have been conducted for level 4 fully autonomous driving. In order for commercialization of the autonomous vehicle, personalized autonomous driving is required to minimize passenger's insecureness to the autonomous vehicle. To address this problem. this study proposes mathematical model that represents driving characteristics and recursive least-squares based algorithm that can estimate the defined characteristics. The actual data of two drivers has been used to derive driving characteristics and the hypothesis testing method has been used to classify two drivers. It is shown that the proposed algorithms can derive driving characteristics and classify two drivers reasonably.
Keywords
Recursive least squares; Hypothesis testing; Driving characteristic; Autonomous driving; Personalization; Convergent algorithm;
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Times Cited By KSCI : 10  (Citation Analysis)
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1 S. Lefevre, A. Cavalho, Y. Gao, H. Tseng, and F. Borrelli, "Driver models for personlised driving assistance", Vehicle System Dynamics, Vol. 53, No. 12, pp.1705-1720, 2015.   DOI
2 S. Lefevre, A. Cavalho, and F. Borrelli, "A Learning-Based Framework for Velocity Control in Autonomous Driving", IEEE Transactions on Automation Science and Engineering, Vol. 13, No. 1, pp.32-42, 2016.   DOI
3 V. Butakov and P. Loannou, "Driving Autopilot with Personalization Feature for Improved Safety and Comfort", Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on, pp.387-393, 2015.
4 M. Cunningham and M. Regan, "Autonomous vehicles: human factors issues and future research", Proceedings of the 2015 Australasian Road Safety Conference, 2015.
5 T. Mioch, L. Kroon, and M. Neerincx, "Driver Readiness Model for Regulating the Transfer from Automation to Human Control", Proceedings of the 22nd International Conference on Intelligent User Interfaces, pp. 205-213, 2017.
6 S. Jung, "IT Convergence UAV Swarm for Aerial Advertising", J. of the Korea Convergence Society, Vol. 8, No. 4, pp. 183-188, 2017.   DOI
7 S. Jung, "The Control of Spring-Mass-Damper Convergence System using $H{\infty}$ Controller and $\mu$-Synthesis Controller", J. of the Korea Convergence Society, Vol. 8, No. 5, pp. 1-11, 2017.   DOI
8 J. Park, B. Kim, J. Shen, and D. Rho, "Development of Remote Monitoring and Control Device of 50KW Photovoltaic System", J. of the Korea Convergence Society, Vol. 2, No. 3, pp. 7-14, 2011.
9 G. Kim and J. Han, "Unsupervised Machine Learning based on Neighborhood Interaction Function for BCI(Brain-Computer Interface)", J. of Digital Convergence, Vol. 13, No. 8, pp. 298-294, 2015.
10 J. Ku, "A Study on the Machine Learning Model for Product Faculty Prediction in Internet of Things Environment", J. of Convergence for Information Technology, Vol. 7, No. 1, pp. 55-60, 2017.   DOI
11 D. Choi and J. Park, "Security Tendency Analysis Techniques Through Machine Learning Algorithms in Big Data Environments", J. of Digital Convergence, Vol. 13, No. 9, pp. 269-276, 2015.   DOI
12 Y. Yun, "Development of Smart Senio Classification Model based on Activity Profile Using Machine Learning Method", J. of Digital Convergence, Vol. 8, No. 1, pp. 25-34, 2017.
13 H. Lee, S. Chung, and E. Choi, "A Case Study on Machine Learning Applications and Performance Improvement in Learning Algorithm", J. of Digital Convergence, Vol. 14, No. 2, pp. 245-258, 2016.   DOI
14 B. Hwang and S. Kim, "On Implementing a Learning Environment for Big Data Processing using Raspberry Pi", J. of Digital Convergence, Vol. 14, No. 4, pp. 251-258, 2016.   DOI
15 Y. Ki and Jong Lim, "Lip Reading Method Using CNN for Utterance Period Detection", J. of Digital Convergence, Vol. 14, No. 8, pp. 233-243, 2016.   DOI
16 S. Moon and K. Yi, "Human driving data-based design of a vehicle adaptive cruise control algorithm", Vehicle System Dynamics, Vol. 46, No. 8, pp. 661-690, 2008.   DOI