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Statistical and biomechanical prediction of automobile driving posture.

机译:汽车行驶姿态的统计和生物力学预测。

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摘要

Automobile interiors are increasingly designed with the aid of three-dimensional computer-rendered representations of the human body, but the use of these models is hampered by the lack of accurate posture prediction. This research develops and evaluates statistical models to predict static driving posture and proposes a general theory of driving posture selection based on a muscle-activity-reduction criterion.; The effects of vehicle and seat geometry on driving posture were examined in reconfigurable vehicle mockups and vehicles. The postures of 84 drivers spanning a wide range of body size were recorded in the mockups for various combinations of seat height, steering wheel position, seat cushion angle, and downward vision restriction. The postures of 120 men and women were recorded in five vehicles after a 15-minute drive. Drivers adapt to changes in the vehicle and seat geometry primarily by changing limb posture. Each of the test variables has significant effects on driving posture that are independent of anthropometry.; Three alternative whole-body posture prediction models developed from the laboratory data were assessed by comparing model-predicted driver eye locations with observed in-vehicle eye locations. The average eye-location error for the model that combines direct prediction of eye and hip locations with inverse kinematics is less than 4 mm horizontally and less than 7 mm vertically. Prediction of mean postures for population groups is considerably more accurate than the prediction of individuals' postures.; In an electromyographic study, the average driving posture chosen by 10 men was generally consistent with the hypothesis that drivers tend to select torso postures with the highest eye location that can be achieved with low levels of thoracolumbar extensor muscle activity. Biomechanical simulations demonstrated that passive lumbar flexion stiffness may contribute significantly to the stability of the upper body in driving postures.; This research quantified the effects the driving environment on whole-body driving posture and developed new insight into torso posture selection. The findings improve the utility of human models for vehicle ergonomic assessment and contribute to an improved understanding of human adaptation to task environments.
机译:汽车内饰越来越多地借助计算机对人体的三维三维表示来进行设计,但是由于缺乏准确的姿势预测,因此无法使用这些模型。这项研究开发并评估了预测静态驾驶姿势的统计模型,并提出了基于减少肌肉活动标准的驾驶姿势选择的一般理论。在可重构的车辆模型和车辆中检查了车辆和座椅几何形状对驾驶姿势的影响。在样机中记录了84名驾驶员的姿势,这些姿势涵盖了各种身材,包括座椅高度,方向盘位置,座垫角度和向下视线限制的各种组合。在开车15分钟后,五辆车记录了120名男女的姿势。驾驶员主要通过改变肢体姿势来适应车辆和座椅几何形状的变化。每个测试变量对驾驶姿势都有重要影响,而与人体测量法无关。通过将模型预测的驾驶员眼睛位置与观察到的车内眼睛位置进行比较,评估了根据实验室数据开发的三种替代性全身姿势预测模型。该模型将眼睛和髋部位置的直接预测与反向运动学相结合的模型的平均眼睛位置误差水平小于4毫米,垂直小于7毫米。人口群体平均姿势的预测比个人姿势的预测要准确得多。在一项肌电图研究中,由10名男性选择的平均驾驶姿势通常与以下假设相一致:驾驶者倾向于选择眼部位置最高的躯干姿势,而这些姿势可以通过低水平的胸腰椎伸肌活动来实现。生物力学模拟表明,被动腰部弯曲刚度可能在驾驶姿势中极大地有助于上身的稳定性。这项研究量化了驾驶环境对全身驾驶姿势的影响,并为躯干姿势选择开辟了新见识。这些发现提高了人类模型在车辆人体工程学评估中的效用,并有助于人们更好地了解人类对任务环境的适应性。

著录项

  • 作者

    Reed, Matthew Paul.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Engineering Biomedical.; Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1998
  • 页码 234 p.
  • 总页数 234
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物医学工程;一般工业技术;
  • 关键词

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