为电动自行车骑手优化车辆前端结构安全:使用伤害预测模型的先进多目标方法
Qiang Wang1, Boxuan Yu1, Yu Liu2
1Country State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle, Hunan University, Changsha, Hunan, 410082, China.
Accident; analysis and prevention
|August 30, 2024
概括
本研究引入了一种利用伤害预测的优化方法,以提高电动自行车骑手在汽车碰撞中的安全性. 这种方法提高了车辆前端的设计,有效地降低了骑手受伤的风险.
科学领域:
- 道路安全工程工程 道路安全工程
- 生物机械分析分析
- 计算建模计算建模
背景情况:
- 中国越来越多的电动自行车使用凸显了乘客安全的关键问题.
- 现有的车辆设计在碰撞时对电动自行车骑手提供了不足的保护.
研究的目的:
- 开发一种多目标优化方法,以提高电动自行车骑手的车辆前端保护.
- 通过改进车辆设计,减少车辆与电动自行车碰撞中骑手受伤的严重程度.
主要方法:
- 使用自动化Madymo模拟收集了大规模的骑手伤害反应数据.
- 开发了一种机器学习模型,用于预测不同碰撞条件下的骑手受伤风险.
- 将伤害预测模型集成到多目标优化框架中,并进行多标准决策分析.
主要成果:
- 确定了关键的设计变量,包括引擎盖前部高度和保险宽度,以进行优化.
- 通过优化车辆前端设计,显著降低了骑手受伤风险.
- 展示了该方法在不同身体部位之间平衡受伤风险的能力.
结论:
- 建议的优化方法有效指导车辆设计,以提高电动自行车骑手的安全性.
- 该方法为减少汽车与电动自行车碰撞中的伤害提供了可操作的见解.
- 这项研究为加强对弱势道路使用者的保护措施提供了一条途径.
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