在三维世界中导航时,与环境中的对象保持适当间隙的能力很重要。先前的研究表明,引导/接近物体对向的视角及其变化率是定时拦截的重要变量,防撞,制动的连续调节,和手动控制的头。然而,航向维护的调查要求参与者保持固定的航向距离,并且没有调查如何考虑有关自身速度的信息。在下面的实验中,我们要求参与者使用操纵杆跟踪计算机模拟的铅物体.结果表明,跟随速度,并且铅物体的大小对平均跟随距离和跟随距离方差都有显着影响。此外,当假设引导对象的期望视觉范围会随时间变化时,参与者的操纵杆响应模型提供了更好的拟合。一起来看,结果表明,当控制器使用有关自身速度的信息来设置所需的航向目标时,间距的连续调节主要受引导物体的视角及其变化率的影响。对视角的依赖,它的变化率,和/或自身速度信息也根据系统的控制动态而变化。这些发现与最优控制标准一致,该标准反映了根据工厂动态对不同信息源的不同加权。与其他对运动的深度判断一样,用于控制与环境中其他对象的进度的信息取决于任务的约束和不同的控制策略。
The ability to maintain appropriate gaps to objects in one\'s environment is important when navigating through a three-dimensional world. Previous research has shown that the visual angle subtended by a lead/approaching object and its rate of change are important variables for timing interceptions, collision avoidance, continuous regulation of braking, and manual control of headway. However, investigations of headway maintenance have required participants to maintain a fixed distance headway and have not investigated how information about own-speed is taken into account. In the following experiment, we asked participants to use a joystick to follow computer-simulated lead objects. The results showed that ground texture, following speed, and the size of the lead object had significant effects on both mean following distances and following distance variance. Furthermore, models of the participants\' joystick responses provided better fits when it was assumed that the desired visual extent of the lead object would vary over time. Taken together, the results indicate that while information about own-speed is used by controllers to set the desired headway to a lead object, the continuous regulation of headway is influenced primarily by the visual angle of the lead object and its rate of change. The reliance on visual angle, its rate of change, and/or own-speed information also varied depending on the control dynamics of the system. Such findings are consistent with an optimal control criterion that reflects a differential weighting on different sources of information depending on the plant dynamics. As in other judgements of motion in depth, the information used for controlling headway to other objects in the environment varies depending on the constraints of the task and different strategies of control.