高速公路自动变道过程中乘客的舒适度:斯图加特驾驶模拟器中不同变道轨迹的主题研究

Christoph Heimsath, Werner Krantz, Jens Neubeck, Christian Holzapfel, Andreas Wagner
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摘要

本文介绍了斯图加特全尺寸移动驾驶模拟器最近的一项主题研究的设置和结果。这项研究的重点是在高速双车道高速公路场景中自动变道时乘客的舒适度。该场景包含不同的对称和非对称变道轨迹、弯道和路面质量。每个不对称轨迹被分为具有不同特征的两部分。受试者在每次变道后直接在平板电脑上输入他们对舒适度的主观印象。车辆离开前一车道的阶段和车辆到达目标车道的阶段分别进行评级。这使得能够对不对称变道轨迹形状的两个特征部分进行详细的效果分析。即使在微小的客观变化下,该评估方法也能够确定主观差异。结果分析验证了描述轨迹特征的客观标准与主观舒适度评级之间的相关性。此外,还确定了弯曲引起的主观评级偏差。研究结果促使非对称变道轨迹的曲率依赖性使用,以在不降低纵向速度或增加变道持续时间的情况下提高舒适度,从而在需要切入的交通空间方面保持交通效率。研究数据进一步用于开发自动驾驶功能的乘客舒适度指标。
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Passengers comfort during automated motorway lane changes: a subject study on different lane change trajectories at the Stuttgart driving simulator

This article presents the setup and results of a recent subject study at the full-scale moving Stuttgart driving simulator. The study focusses on the passenger’s comfort during automated lane changes in a high-speed two-lane motorway scenario. The scenario contains different symmetric and asymmetric lane change trajectories, bends and road surface qualities. Each asymmetric trajectory is divided into two parts with different characteristics. The subjects input their subjective impression of comfort directly after each lane change on a tablet computer. The phase in which the vehicle leaves its previous lane and the phase in which the vehicle arrives at its target lane are rated individually. This enables a detailed effect analysis for the two characteristic parts of asymmetric lane change trajectory shapes. The evaluation method is able to determine subjective differences even at small objective changes. Result analysis verifies correlations between objective criteria describing the trajectory characteristics and the subjective comfort ratings. In addition, a curvature caused bias on the subjective ratings in bends is determined. The results motivate the curvature-dependent use of asymmetric lane change trajectories to improve comfort without reducing longitudinal velocity or increase lane change duration and thus maintaining traffic efficiency in terms of required traffic interspaces to cut in. The study data is further used for the development of a passengers’ comfort metric for automated driving functions.

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