Multi-TPER

Exploring the Impact of Drivers' Emotion and Multi-task Learning on Takeover Behavior Prediction in Multimodal Environment

Introduction

EmoTake is a deep learning-empowered system that explores drivers’ emotional and physical states to predict takeover readiness, reaction time, and quality.

Running

The dataset used in this project comes from EmoTake.

Citation

If you find this work helpful, please consider citing the following papers.

@article{gu2024emotake,
  title={EmoTake: Exploring Drivers' Emotion for Takeover Behavior Prediction},
  author={Gu, Yu and Weng, Yibing and Wang, Yantong and Wang, Meng and Zhuang, Guohang and Huang, Jinyang and Peng, Xiaolan and Luo, Liang and Ren, Fuji},
  journal={IEEE Transactions on Affective Computing},
  year={2024},
  publisher={IEEE}
}

Concact

If you have any questions or want to use the code, feel free to contact:

• Yu Gu: ([email protected])
• Xinyu Feng: ([email protected])