Influence of multi-modal warning interface on takeover efficiency of autonomous high-speed train
As a large-scale public transport mode, the driving safety of high-speed rail has a profound impact on public health. In this study, we determined the most efficient multi-modal warning interface for automatic driving of a high-speed train and put forward suggestions for optimization and improvement...
Main Authors: | Jing, Chunhui, Dai, Haohong, Yao, Xing, Du, Dandan, Yu, Kaidi, Yu, Dongyu, Zhi, Jinyi |
---|---|
Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/169585 |
Similar Items
-
A personalized behavior learning system for human-like longitudinal speed control of autonomous vehicles
by: Lu, Chao, et al.
Published: (2020) -
Prioritized experience-based reinforcement learning with human guidance for autonomous driving
by: Wu, Jingda, et al.
Published: (2024) -
Safety-aware human-in-the-loop reinforcement learning with shared control for autonomous driving
by: Huang, Wenhui, et al.
Published: (2025) -
Interactive prediction and decision-making for autonomous vehicles: online active learning with traffic entropy minimization
by: Zhang, Yiran, et al.
Published: (2025) -
Application of deep learning for enhancing simultaneous localization and mapping in autonomous driving
by: Ge, Jintian
Published: (2024)