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Proceedings Paper

Design method of machine-learning system used for autonomous land vehicle
Author(s): Han-gen He; Wensen Chang
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Paper Abstract

The control of Autonomous Land Vehicle (ALV) is a kind of typical nonlinear control. Because the state of traffic and road are complex, so the control of ALV is complex and uncertain. Especially if the ALV runs in normal state of traffic, the control of ALV is becoming more complex and difficult. A good idea is that to let the control system of ALV to simulate human driver and develop a machine-leaning system in the control system of ALV. So that as the control system of ALV is driving ALV along road, the control system can learn from the experience of human driver according to the state of traffic and road. In other words, the control system of ALV is able to become more and more 'clever.' Of course it is a challenging and very difficult task. This paper analyzes the principle of machine-leaning system used for ALV and discusses the engineering method of developing a machine- leaning system used for ALV, when the ALV runs along highway in normal traffic. This paper advances the administrative levels of machine-leaning system and a method of fusing human intelligence into machine intelligence. This paper introduces our preliminary research on machine-leaning system used for ALV also, which is a kind of online machine-leaning system without teacher.

Paper Details

Date Published: 22 July 1999
PDF: 8 pages
Proc. SPIE 3693, Unmanned Ground Vehicle Technology, (22 July 1999); doi: 10.1117/12.354458
Show Author Affiliations
Han-gen He, National Univ. of Defense Technology (China)
Wensen Chang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 3693:
Unmanned Ground Vehicle Technology
Grant R. Gerhart; Robert W. Gunderson; Chuck M. Shoemaker, Editor(s)

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