Driving is a high-demanding task, related to human capacity, required performance and events occurring in the external environment. Mental workload depends on numerous factors: task difficulty, task complexity, level of traffic, additional activities required by the driving action or imposed by the driver, the contextual conditions, as well as the individual response to stress. The study of driver's workload is crucial in guiding future car design, in order to improve the user experience, comfort as well as driving performance and safety. Indeed, if task demands are too high in relation to the user's capabilities, errors may occur and may become critical for safety. The present paper defines a transdisciplinary approach based on monitoring the driver's workload during driving tasks in order to map the perceived user experience, and finally understand the interaction between the driver and the car systems. The approach is based on three layers: the human conditions to detect, the vital parameters to be monitored, and the adopted monitoring technologies. The paper proposes: a protocol to monitor the driver's workload during both real and simulated tasks, a technological set-up including physiological and performance data collection, and a proper data elaboration strategy. The key findings are: the selection of the most relevant subjective and objective parameters to measure the driver's mental workload, the definition of a preliminary technological set-up for monitoring the workload during simulated driving, and the evaluation of the effects of task complexity and of a secondary task on driver's performance. The research paved the way to further studies about how to miniaturize and embed sensors inside the car for a less intrusive application during real driving. Results can also be used to assess the interaction with car devices and to compare different design alternatives.

驾驶是一项艰巨的任务，与人的能力，所需的性能和外部环境中发生的事件有关。精神工作量取决于许多因素：任务难度，任务复杂性，交通水平，驾驶行为要求或驾驶员施加的其他活动，环境条件以及个人对压力的反应。驾驶员工作量的研究对于指导未来的汽车设计，改善用户体验，舒适性以及驾驶性能和安全性至关重要。实际上，如果任务要求相对于用户能力而言过高，则可能会发生错误，并且可能对安全性至关重要。本文基于监控驾驶任务期间驾驶员的工作量来定义一种跨学科方法，以便绘制感知到的用户体验，最终了解驾驶员与汽车系统之间的相互作用。该方法基于三层：要检测的人体状况，要监视的重要参数以及采用的监视技术。该论文提出：一种协议，用于在实际和模拟任务期间监视驾驶员的工作量；一种包括生理和性能数据收集的技术设置；以及一种适当的数据阐述策略。主要发现是：选择最相关的主观和客观参数以测量驾驶员的心理工作量，定义用于在模拟驾驶过程中监控工作量的初步技术设置，以及评估任务复杂性和对驾驶员的影响。驾驶员表现的次要任务。这项研究为进一步研究如何将传感器小型化和嵌入汽车内铺平了道路，以减少实际驾驶中的干扰性应用。结果还可以用于评估与汽车设备的交互作用，并比较不同的设计方案。