Scholarlink

Automated driving (SAE Level 3 and Level 4) allows drivers to engage in non-driving activities (NDRA). However, current vehicle interiors and safety measures are designed for a specific driving posture, while NDRA introduce varied body postures. Additionally, transitioning from an NDRA back to driving adds further complexity. Testing all possible scenarios in real vehicles is costly and time-consuming, making digital validation using human models essential. This contribution outlines, how DHMs enable systematic monitoring of posture transitions, movement, and timing in NDRA and take-over scenarios. To fully validate automated driving, integrating these models with digital crash dummies and simulation structures is beneficial. This approach may also extend beyond vehicles to assess drivers’ cognitive states. Based on the existing HoMoTo model, a structured scenario description supports this effort. In order to pursue this research objective, a project idea was drafted to advance simulation-based testing and is presented in this contribution. Similar to the SOTIF standard (ISO 21448), this initiative aims to help manufacturers validate NDRA and driver take-overs through simulations.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The Use of Digital Human Models for Passenger Simulation in Automated Vehicles

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Miriam Schäffer,
  • Wolfram Remlinger

摘要

Automated driving (SAE Level 3 and Level 4) allows drivers to engage in non-driving activities (NDRA). However, current vehicle interiors and safety measures are designed for a specific driving posture, while NDRA introduce varied body postures. Additionally, transitioning from an NDRA back to driving adds further complexity. Testing all possible scenarios in real vehicles is costly and time-consuming, making digital validation using human models essential. This contribution outlines, how DHMs enable systematic monitoring of posture transitions, movement, and timing in NDRA and take-over scenarios. To fully validate automated driving, integrating these models with digital crash dummies and simulation structures is beneficial. This approach may also extend beyond vehicles to assess drivers’ cognitive states. Based on the existing HoMoTo model, a structured scenario description supports this effort. In order to pursue this research objective, a project idea was drafted to advance simulation-based testing and is presented in this contribution. Similar to the SOTIF standard (ISO 21448), this initiative aims to help manufacturers validate NDRA and driver take-overs through simulations.