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. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal-Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic-text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory-visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public.Published versionThis work was supported by the National Natural Science Foundation of China (grant number 52175253); The MOE Layout Foundation of Humanities and Social Sciences (grant number 19YJA760094); Project of Sichuan Natural Science Foundation (Youth Science Foundation) (grant number 22NSFSC0865); Project of Sichuan Provincial Key Laboratory of digital media art, Sichuan Conservatory of music (grant number 22DMAKL02); degree and postgraduate education and teaching reform project of Southwest Jiaotong University (grant number YJG5-2022-Y038); and China Academy of Fine Arts Creative Design and Intelligent Laboratory Open Fund Project (Supported by Design-AI lab of China Academy of Art) General Project (grant number CAADAI2022B002)

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. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal–Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic–text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory–visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public

Fine-Grained Tb₃Al₅O₁₂ Transparent Ceramics Prepared by Co-Precipitation Synthesis and Two-Step Sintering

In recent years, transparent terbium aluminum garnet (TAG) ceramics have attracted much attention for use in high-power Faraday isolators. Fine-grained ceramics usually possess better mechanical properties and accordingly better service performance. In this work, transparent TAG ceramics with fine grains were prepared using a two-step sintering procedure based on the low-temperature sintering process to suppress grain growth. The composition of TAG precursor and powders calcined at different temperatures was studied in detail. The microstructure and relative density of air pre-sintered TAG ceramics were studied to meet the requirements of hot isostatic pressing (HIP) post-treatment. Driven by the low pre-sintering temperature in air, the average grain sizes of the obtained TAG ceramics after HIP treatment are about 2.9–5.3 μm. The TAG ceramics (1.2 mm thick) pre-sintered at 1450 °C with HIP post-treatment at 1550 °C for 3 h under a 176 MPa Ar atmosphere possess the highest in-line transmittance of 80.3% at 1064 nm. The Verdet constant of the TAG ceramics at 632.8 nm is −180.5 rad·T−1·m−1 at room temperature, which is about 1.3 times larger than that of the commercial Tb3Ga5O12 single crystals