基于汽车操纵动力学的神经网络驾驶员模型
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The artificial neural network driver model based on vehicle handling dynamics
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    摘要:

    作为人一车—路闭环系统的重要环节,驾驶员模型对汽车闭环系统仿真和汽车主动安全性评价都具有重要的意义.本文基于汽车操纵动力学,预瞄—跟随理论以及神经网络建立了一种驾驶员方向控制模型,即两层前馈神经网络驾驶员模型,并在此基础上建立了驾驶员—汽车闭环系统模型.对该闭环模型进行了单移线与双移线仿真试验,仿真结果与理想数据具有很好的一致性,表明该驾驶员模型是合理的,可以有效地模拟驾驶员控制汽车方向的行为特性,为进一步研究人一车一路闭环系统提供了一条可行途径.

    Abstract:

    As a crucial link of the drivervehicleroad closedloop system, the driver model plays an important role in the simulation of vehicle closeloop system and the evaluation of vehicle active safety. Based on the Vehicle Handling Dynamics, the PreviewFollow theory and the Artificial Neural Network, this paper established a directional control driver model—TwoLayerFeedforward Artificial Neural Network Driver Model and the drivervehicle closed-loop system model. Using the closeloop system model, single and double lane change simulations were performed. The results show good agreement with the ideal data. It indicates that this driver model is reasonable enough to simulate the driver’s behavior property and provide a feasible way to the further investigation of the drivervehicleroad closedloop system.

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徐瑾,赵又群,阮米庆.基于汽车操纵动力学的神经网络驾驶员模型[J].动力学与控制学报,2008,6(4):381~384; Xu Jin, Zhao Youqun, Ruan Miqing. The artificial neural network driver model based on vehicle handling dynamics[J]. Journal of Dynamics and Control,2008,6(4):381-384.

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  • 收稿日期:2008-09-09
  • 最后修改日期:2008-09-23
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