College of Mechanical and Material Engineering, North China University of Technology, Beijing, China.
School of International Art Education, Tianjin Academy of Fine Arts, Tianjin, China.
Front Public Health. 2022 Feb 14;10:813859. doi: 10.3389/fpubh.2022.813859. eCollection 2022.
Carsharing scale has been increasing rapidly with sharing economy. However, many users are reluctant to rent cars any longer due to the low-quality of interactive experience and usability, especially in terms of the dashboard design. This challenge should be urgently addressed in order to maintain the sustainable development of car-sharing industry and its environmental benefits. This study aims to investigate the relationship between users' driving activities (e.g., searching time, reading time, eye movement, heart rate) and dashboard layout. This study was conducted based on the experimental investigation among 58 respondents who were required to complete driving tasks in four types of cars with different dashboard layouts. Afterwards, a prediction model was developed to predict users heart rate (HR) based on the long short-term memory model, and logistic models were used to examine the relationship between the occurrence probability of minimum HR and dashboard reading. The results showed that the system usability of a dashboard was related to the drivers' eye movement characteristics including fixation duration, fixation times and pupil diameter. Most indicators had significant effects ( < 0.05) on the system usability score of corresponding dashboard. The long short-term memory model network (RMSE = 1.105, MAE = 0.009) was capable of predicting heart rate (HR) that happened in the process of instrument reading, which presented a periodic pattern rather than a continuous increase or decrease. It reflected that the network could better fit the non-linear and time-sequential laws of HR data. Furthermore, the probability of the lowest heart rate occurrence during the interaction with four dashboards was influenced by the average searching time, reading time and reading accuracy that were related to a specific layout. Overall, this study provided a theoretical reference for uncovering users' adaptive behaviors with the central control screen and for the optimal choice of a suitable dashboard layout in interface design.
汽车共享规模随着共享经济的发展迅速增长。然而，由于交互体验和可用性质量低下，尤其是仪表盘设计，许多用户不再愿意租车。为了保持汽车共享行业及其环境效益的可持续发展，这一挑战亟待解决。本研究旨在调查用户驾驶活动（例如搜索时间、阅读时间、眼动、心率）与仪表盘布局之间的关系。本研究基于对 58 名受访者的实验调查，要求他们在四种具有不同仪表盘布局的汽车中完成驾驶任务。之后，开发了一个预测模型，基于长短期记忆模型预测用户的心率（HR），并使用逻辑模型来检验最小 HR 发生概率与仪表盘读数之间的关系。结果表明，仪表盘的系统可用性与驾驶员的眼动特征有关，包括注视持续时间、注视次数和瞳孔直径。大多数指标对相应仪表盘的系统可用性评分有显著影响（<0.05）。长短期记忆模型网络（RMSE=1.105，MAE=0.009）能够预测在仪表读数过程中发生的心率（HR），其呈现周期性模式，而不是连续增加或减少。这表明该网络能够更好地拟合 HR 数据的非线性和时间序列规律。此外，在与四个仪表盘交互过程中发生最低心率的概率受到平均搜索时间、阅读时间和阅读准确性的影响，这些因素与特定的布局有关。总的来说，本研究为揭示用户与中央控制屏幕的适应行为以及为界面设计中选择合适的仪表盘布局提供了理论参考。
