Automatic Navigation of Intelligent Vehicle Control System Based on Laser Sensor

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Abstract:

This smart car control system by MC9S12G128 controller as the core, the use of a row of 18 laser tubes and 6 receiving tube as the path recognition sensor, through MC9S12G128 I / 0 interface for sensor signal, and use the feature extraction method to extract the track type, realization of the starting line, cross line recognition. According to road information, the design adopts fuzzy control algorithm of output PWM wave to control the gear steering, complete control of the direction of the car, the car speed extracted with the use of photoelectric encoder, comparing with the current set point to get speed deviation, and output PWM pulse is obtained by using the PID algorithm to control the motor to adjust the car speed, complete the closed-loop control of the car movement speed. Through the experiment, the system is designed to achieve the desired effect.

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Advanced Materials Research (Volumes 1049-1050)

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661-664

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Morten Welde, James Odeck. Evaluating. the Economic Impacts of Intelligent Transport Systems. Proceedings of the 14th World congress on Intelligent Transport System, (2007).

Google Scholar

[2] Bin Lin, Harry H Cheng, Benjamin D Shaw, Joe Palen. Optical and electronic design for a field prototype of a laser-based vehicle delineation detection system . Optics and Lasers in Engineering, Volume 36, Issue 1, July 2001, Pages 11-27.

DOI: 10.1016/s0143-8166(01)00046-x

Google Scholar

[3] Xiao xiong Weng, Guangzhai Luo. Intelligent Traffic Information Systems base on feature of traffic flow. Proceedings of the 14th World congress on Intelligent Transport System, (2007).

Google Scholar

[4] D. Martín, F. García, B. Musleh, D. Olmeda, G. Peláez, P. Marín, A. Ponz, C. Rodríguez, A. Al-Kaff, A. de la Escalera, J.M. Armingol . An intelligent vehicle based on computational perception. Expert Systems with Applications, Volume 41, Issue 17, 1 December 2014, Pages 7927-7944.

DOI: 10.1016/j.eswa.2014.07.002

Google Scholar

[5] M. Reze, M. Osajda. 2 - MEMS sensors for automotive vehicle stability control applications. Mems for Automotive and Aerospace Applications, 2013, Pages 29-53.

DOI: 10.1533/9780857096487.1.29

Google Scholar