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《Journal of South China University of Technology(Natural Science Edition)》 2016-12
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A Neural Network-Based Autonomous Articulated Vehicle System Considering Driver Behavior

ZHANG Wen-ming;HAN Hong-bing;YANG Jue;YI Xiao;School of Mechanical Engineering,University of Science and Technology Beijing;  
In view of the steering characteristics of articulated dump trucks,an autonomous articulated vehicle system is proposed based on neural networks and by considering driver behaviors. First,a sensor collecting system based on the laser radar and the angular transducer is established,and an articulated vehicle kinematics model and a dynamics model of articulated dump trucks are constructed by analyzing the steering characteristics of articulated dump trucks. Then,by using the ADAMS software,a dynamic model of the trucks is constructed to perform a steady state test. Moreover,a driver model of the artificial neural network control algorithm is constructed based on the optimal preview control,and it is verified by an Adams-Matlab / Simulink co-simulation. Finally,this control model is also verified by establishing a simulation ground tunnel to perform the straight-road-return and curve-roadfollowing tests. The results show that,when the constructed control model is applied to the variable curvature road,the lateral position error is less than 10% of the passable distance,and 90% of the course angle deviation is optimized,which indicates that the constructed control model has a high convergence speed,a good steady state and an excellent unmanned driving performance.
【Fund】: 国家高技术研究发展计划(863计划)项目(2011AA060404)~~
【CateGory Index】: U463.6
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