AV-TLX：用于测量自动驾驶车辆驾驶（脑力）工作负荷的工具——源自NASA-TLX，专为自动驾驶时代开发
AV-TLX for measuring (mental) workload while driving AVs: Born from NASA-TLX but developed for the era of automated vehicles
AI总结：
本研究提出AV-TLX，一种专为L3级自动驾驶设计的工作负荷测量工具，通过文献综述和定性开发，经模拟器验证具有高信度（0.86）和效度，支持总体及分维度评估。
摘要：
自动驾驶车辆的引入重新定义了驾驶员与车辆之间的交互水平，带来了新的任务，并因此施加了不同的工作负荷。现有的工具如NASA-TLX和DALI仍被用于评估自动驾驶车辆中的驾驶工作负荷，尽管它们并未考虑这些新任务。本研究介绍了AV-TLX，一种专门用于测量L3级自动驾驶工作负荷的工具。开发过程始于一项叙述性文献综述，以识别影响工作负荷的主要因素。随后进行了一系列定性会议，在此期间设计了问卷的维度及后续的问题。该工具的有效性首先通过CVR和CVI指数进行评估，其信度和收敛效度则通过高保真动态驾驶模拟器进行评估。AV-TLX的最终版本包含8个子量表下的19个问题，表现出优异的信度（0.86）和效度（CVR > 0.78）。在模拟研究中，AV-TLX与NASA-TLX结果之间的一致性得分为0.6，这被认为是两份问卷一致性可接受的水平。此外，该问卷有两种使用方式：一是报告总体工作负荷和/或分为8个主要子量表，二是将问题分为两组，包括接管任务工作负荷和自动驾驶任务工作负荷。论文中呈现的最终版问卷可供未来聚焦于L3级自动驾驶的研究使用。
英文摘要：
The introduction of automated vehicles has redefined the level of interaction between the driver and the vehicle, introducing new tasks and so impose different workloads. Existing tools such as NASA-TLX and DALI are still used to assess driving workload in automated vehicles, despite not accounting for new tasks. This study introduces AV-TLX, a specialized tool for measuring workload in Level 3 automated driving. The development process began with a narrative literature review to identify the primary factors influencing workload. This was followed by a series of qualitative sessions during which the dimensions and later the questions of the questionnaire were designed. The tools validity was first assessed using CVR and CVI indices, and its reliability and convergent validity were evaluated using a dynamic driving simulator with high fidelity. The final version of AV-TLX comprises 19 questions across 8 subscales, demonstrating excellent reliability (0.86) and validity (CVR > 0.78). An agreement scores between the results of AV-TLX and NASA-TLX in the simulation study was 0.6, which is considered acceptable for the consistency of two questionnaires. Furthermore, this questionnaire can be utilized in two ways. First by reporting the overall workload and/or divided into 8 primary subscales, or by categorizing the questions into two groups including takeover task workload and automated driving task workload. The final version of this questionnaire, as presented in the paper, is available for use in future studies focusing on Level 3 automated driving.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
