Department of Biostatistics, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA.
Accid Anal Prev. 2010 May;42(3):891-7. doi: 10.1016/j.aap.2009.04.022.
In driving studies based on simulators and instrumented vehicles, specific models are needed to capture key aspects of driving data such as lateral control. We propose a model that uses weighted polynomial projections to predict each data point from the previous three time points, and accommodates the attempts of the drivers to re-center the vehicle before crossing the borders of the traffic lane. Our model also allows the possibility that average position within the lane may vary from driver to driver. We demonstrate how to fit the model using standard statistical procedures available in software packages such as SAS. We used a fixed-base driving simulator to obtain data from 67 drivers with Alzheimer's disease and 128 elderly drivers without dementia. Using these data, we estimated the subject-specific parameters of our model, and we compared the two groups with respect to these parameters. We found that the parameters based on our model were able to distinguish between the groups in an interpretable manner. Hence, this model may be a useful tool to define outcome measures for observational and interventional driving studies.
在基于模拟器和仪器化车辆的驾驶研究中，需要特定的模型来捕捉驾驶数据的关键方面，例如横向控制。我们提出了一种模型，该模型使用加权多项式投影来从前三个时间点预测每个数据点，并适应驾驶员在越过交通车道边界之前重新将车辆居中的尝试。我们的模型还允许车道内的平均位置可能因驾驶员而异的可能性。我们展示了如何使用 SAS 等软件包中提供的标准统计程序来拟合模型。我们使用固定基础驾驶模拟器从 67 名患有阿尔茨海默病的驾驶员和 128 名无痴呆的老年驾驶员中获得数据。使用这些数据，我们估计了我们模型的特定于主体的参数，并根据这些参数对两组进行了比较。我们发现，基于我们模型的参数能够以可解释的方式区分两组。因此，该模型可能是定义观察性和干预性驾驶研究结果衡量指标的有用工具。
