Analysis of Vehicle Following Behavior of Human Driver Based on Hybrid Dynamical System Model
Analysis of Vehicle Following Behavior of Human Driver Based on Hybrid Dynamical System Model
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DOI：
10.1109/cca.2007.4389404
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发表时间：
2007-11
期刊：
影响因子：
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通讯作者：
T. Akita;S. Inagaki;Tatsuya Suzuki;S. Hayakawa;N. Tsuchida
中科院分区：
文献类型：
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作者：
T. Akita;S. Inagaki;Tatsuya Suzuki;S. Hayakawa;N. Tsuchida
本文介绍了基于混合动力系统（HDS）表达的人类驾驶行为建模的发展，重点关注驾驶员的车辆跟随任务。驾驶数据是通过使用驾驶模拟器收集的，该模拟器可以为驾驶员提供立体沉浸式视觉。在我们的建模中，测量的感觉信息和驾驶员的输出之间的关系表示的分段ARX（PWARX）模型，这是一个类的HDS。作为感觉输入，考虑车辆之间的距离、距离变化率和前车后方面积的时间导数（称为KdB）。此外，踏板操作被认为是输出。将数据聚类和支持向量机相结合，解决了PWARX模型的辨识问题。通过引入PWARX模型，不仅可以从测量的驾驶数据中找到在每个模式中的运动中出现的参数，而且可以找到它们之间的逻辑切换（决策）条件中的参数。从所获得的结果中发现，驾驶员根据感觉信息适当地切换一些"控制律"，特别是KdB在决策中起着重要作用，即，模式之间的切换。
This paper presents the development of the modeling of human driving behavior based on an expression as a hybrid dynamical system (HDS) focusing on the driver's vehicle following task. The driving data are collected by using a driving simulator which can provide a stereoscopic immersive vision to the driver. In our modeling, the relationship between the measured sensory information and the output of the driver are expressed by the piecewise ARX (PWARX) model, which is a class of the HDS. As the sensory input, the range between vehicles, range rate, and time derivative of the area of the back of the preceding vehicle (called KdB) are considered. Furthermore, the pedal operation is considered as the output. The identification problem for the PWARX model is solved using the combination of the data clustering and support vector machine. By introducing the PWARX model, it becomes possible to find not only parameters appearing in the motion in each mode but also parameters in the logical switching (decision making) conditions among them from the measured driving data. From the obtained results, it is found that the driver appropriately switches some "control laws" according to the sensory information, in particular, the KdB plays an important role in the decision making, i.e., the switching between modes.