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An algorithm for combining autonomous vehicles and controlled events in driving simulator experiments

机译:在驾驶模拟器实验中组合自动驾驶汽车和受控事件的算法

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摘要

Autonomous vehicles can be used to create realistic simulations of surrounding vehicles in driving simulators. However, the use of autonomous vehicles makes it difficult to ensure reproducibility between subjects. In this paper, an effort is made to solve the problem by combining autonomous vehicles and controlled events, denoted plays. The aim is to achieve the same initial play conditions for each subject, since the traffic situation around the subject will be dependant upon each subject's actions while driving in the autonomous traffic. This paper presents an algorithm that achieves the transition from autonomous traffic to a predefined start condition for a play. The algorithm has been tested in the VTI driving simulator III with promising results. In most of the cases the algorithm could reconstruct the specified start condition and conduct the transition from autonomous to controlled mode in a non-conspicuous way. Some problems were observed regarding moving unwanted vehicles away from the closest area around the simulator vehicle, and this part of the algorithm has to be enhanced. The experiment also showed that the controlled every-day life traffic normally used in the VTI driving simulator makes subjects drive faster than in autonomous traffic.
机译:可以使用自动驾驶在驾驶模拟器中创建周围车辆的逼真的模拟。然而,自动驾驶车辆的使用使得难以确保对象之间的再现性。在本文中,通过结合自动驾驶车辆和受控事件(表示为比赛),努力解决该问题。目的是为每个受试者实现相同的初始游戏条件,因为在自动驾驶中驾驶时,受试者周围的交通状况将取决于每个受试者的动作。本文提出了一种算法,该算法可实现从自主流量过渡到播放的预定义开始条件。该算法已在VTI驾驶模拟器III中进行了测试,结果令人满意。在大多数情况下,算法可以重构指定的开始条件,并以不明显的方式进行从自主模式到受控模式的转换。在将不需要的车辆从模拟器车辆周围的最近区域移开时,观察到一些问题,并且必须增强算法的这一部分。实验还表明,通常在VTI驾驶模拟器中使用的受控的日常生活交通量使受试者的驾驶速度比自主交通中的驾驶速度更快。

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