我们的论文被IJHCI接收
我们的论文 Modeling Driver Situational Awareness in Takeover Scenarios Using Multimodal Data and Machine Learning 已正式发表于 JCR Q1 期刊 International Journal of Human–Computer Interaction。
- 论文题目
- Modeling Driver Situational Awareness in Takeover Scenarios Using Multimodal Data and Machine Learning
- 作者
- Lesong Jia, Na Du
- 摘要
- In conditionally automated driving, drivers out of the control loop may lack situational awareness (SA), leading to inappropriate takeovers. Monitoring a driver's SA and providing alerts for overlooked objects is critical to enhancing the takeover safety and efficiency. This study aimed to construct predictive models for drivers' SA of objects during takeover transitions. The model features include drivers' physiological data before and after takeover requests as well as the environment and object attributes. The ground truth was obtained through a scene reconstruction task, yielding binary SA labels. The Support Vector Machine delivered the best model performance, achieving a macro F1 score of 0.75 and an accuracy of 0.77, when applied with a time window of 2-second pre-takeover request and 4-second post-takeover request. Our model predicts drivers' SA of specific objects across diverse traffic conditions using short time windows, supporting timely and generalizable driver monitoring and takeover assistance.