机译:预测机动车碰撞事故受害者受伤风险的计算方法:改进高级自动碰撞通知系统的框架
University of Virginia, Center for Applied Biomechamcs, 4040 Lewis and Clark Drive, Charlottesville, VA 22911, USA;
University of Virginia, Center for Applied Biomechamcs, 4040 Lewis and Clark Drive, Charlottesville, VA 22911, USA;
University of Alabama at Birmingham, University Transportation Center, 933 19th Street South, Birmingham, Al 35205, USA;
University of Alabama at Birmingham, University Transportation Center, 933 19th Street South, Birmingham, Al 35205, USA;
University of Alabama at Birmingham, University Transportation Center, 933 19th Street South, Birmingham, Al 35205, USA;
University of Alabama at Birmingham, University Transportation Center, 933 19th Street South, Birmingham, Al 35205, USA;
computational occupant injury-risk restraints multibody;
机译:基于伤害严重性,时间敏感性和可预测性的高级自动碰撞通知算法改进了机动车碰撞乘员分类
机译:预测轻型汽车碰撞后的严重头部伤害:对自动碰撞通知系统的影响。
机译:先进的自动碰撞通知系统的各种高严重性伤害风险阈值的优点和缺点
机译:乘员运输决策算法:开发和评价机动车辆撞车乘机的先进自动碰撞通知算法
机译:重型车辆崩溃安全:提高正面碰撞测试中的胸损伤预测
机译:血液中的酒精水平是否可以很好地预测机动车碰撞受害者的伤害严重程度?
机译:血液中的酒精水平是否可以很好地预测机动车碰撞受害者的伤害严重程度?
机译:使用关联数据评估宾夕法尼亚州211汽车碰撞事故受害者的医院费用。崩溃结果数据评估系统(CODEs)关联数据211示范项目