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首页> 外文期刊>International Journal of Vehicle Autonomous Systems >Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator
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Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

机译：识别驾驶模拟器中遵循随机弯曲路径的五个测试对象的转向控制行为

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The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver.
机译：本文涉及在固定基础驾驶模拟器中使用从五个测试对象获得的数据来识别理论预告转向控制器。对人的转向控制行为的理解与自主和半自主车辆控制的设计有关。驾驶任务涉及沿着随机弯曲的路径操纵线性车辆。从数据中识别出的理论转向控制器基于最佳的线性预览控制。使用直接识别方法，并识别转向控制器，以使预测的转向角尽可能紧密地匹配测试对象的测量转向角。已经发现，识别驾驶员的时间延迟和噪声是避免在识别控制器参数时产生偏差的必要条件。基于车辆的横向/偏航动力学，理论控制器可以很好地预测大多数受试者的转向行为。有证据表明，基于较简单的车辆动力学模型的控制器可以更好地表现经验不足的驾驶员的转向动作，这可能反映了驾驶员的学习不足。

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