Technological advancements focus on developing comfortable and acceptable driving characteristics in autonomous vehicles. Present driving functions predominantly possess predefined parameters, and there is no universally accepted driving style for autonomous vehicles. While driving may be technically safe and the likelihood of road accidents is reduced, passengers may still feel insecure due to a mismatch in driving styles between the human and the autonomous system. Incorporating driving style preferences into automated vehicles enhances acceptance, reduces uncertainty, and poses the opportunity to expedite their adoption. Despite the increased research focus on driving styles, there remains a need for comprehensive studies investigating how variations in the driving context impact the assessment of automated driving functions. Therefore, this work evaluates lateral driving style preferences for autonomous vehicles on rural roads, considering different weather and traffic situations. A controlled study was conducted with a variety of German participants utilizing a high-fidelity driving simulator. The subjects experienced four different driving styles, including mimicking of their own driving behavior under two weather conditions. A notable preference for a more passive driving style became evident based on statistical analyses of participants' responses during and after the drives. This study could not confirm the hypothesis that subjects prefer to be driven by mimicking their own driving behavior. Furthermore, the study illustrated that weather conditions and oncoming traffic substantially influence the perceived comfort during autonomous rides. The gathered dataset is openly accessible at https://www.kaggle.com/datasets/jhaselberger/idcld-subject-study-on-driving-style-preferences.

翻译：技术进步致力于开发自动驾驶汽车中舒适且可接受的驾驶特性。当前驾驶功能主要具有预定义的参数，而自动驾驶汽车尚无普遍接受的驾驶风格。尽管驾驶可能在技术上是安全的，并且道路事故的可能性降低，但乘客仍可能因人类与自动驾驶系统之间的驾驶风格不匹配而感到不安。将驾驶风格偏好融入自动驾驶汽车可提升接受度、减少不确定性，并有望加速其普及。尽管对驾驶风格的研究日益增多，但仍需全面研究探讨驾驶情境变化如何影响自动驾驶功能的评估。因此，本研究评估了乡村道路上自动驾驶汽车的横向驾驶风格偏好，考虑了不同的天气和交通情况。我们利用高保真驾驶模拟器，对多种德国参与者进行了一项受控研究。受试者体验了四种不同的驾驶风格，包括在两种天气条件下模仿自身驾驶行为。根据驾驶过程中及驾驶后参与者反应的统计分析，明显表现出对更被动驾驶风格的偏好。本研究未能证实受试者更倾向于被模仿自身驾驶行为所驾驶的假设。此外，研究表明天气条件和对向交通显著影响自动驾驶过程中的感知舒适度。所收集的数据集可在 https://www.kaggle.com/datasets/jhaselberger/idcld-subject-study-on-driving-style-preferences 公开获取。