Division of Data and Analytics, Virginia Tech Transportation Institute, Blacksburg, VA 24061, United States.
Division of Data and Analytics, Virginia Tech Transportation Institute, Blacksburg, VA 24061, United States.
Accid Anal Prev. 2021 Oct;161:106356. doi: 10.1016/j.aap.2021.106356. Epub 2021 Aug 26.
The purpose of this study is to understand and quantify the simultaneous effects of roadway speed category, driver age, driver gender, vehicle class, and location on the rates of longitudinal and lateral acceleration epochs. The rate of usual as well as harsh acceleration epochs are used to extract insights on driving risk and driver comfort preferences. However, an analysis of acceleration rates at multiple thresholds incorporating various effects while using a large-scale and diverse dataset is missing. This analysis will fill this research gap. Data from the 2nd Strategic Highway Research Program Naturalistic Driving Study (SHRP2 NDS) was used for this analysis. The rate of occurrence of acceleration epochs was modeled using negative binomial distribution based generalized linear mixed effect models. Roadway speed category, driver age, driver gender, vehicle class, and location were used as the fixed effects and the driver identifier was used as the random effect. Incidence rate ratios were then calculated to compare subcategories of each fixed effect. Roadway speed category has the strongest effect on longitudinal and lateral accelerations of all magnitudes. Acceleration epoch rates consistently decrease as the roadway speed category increases. The difference in the rates depends on the threshold and is up to three orders of magnitude. Driver age is another significant factor with clear trends for longitudinal and lateral acceleration epochs. Younger and older drivers experience higher rates of longitudinal accelerations and decelerations. However, the rate of lateral accelerations consistently decreases with age. Vehicle class also has a significant effect on the rate of harsh accelerations with minivans consistently experiencing lower rates.
本研究旨在理解和量化道路速度类别、驾驶员年龄、性别、车辆类型和位置对纵向和横向加速度时段率的同时影响。通常和苛刻的加速时段率用于提取驾驶风险和驾驶员舒适偏好的见解。然而，在使用大规模和多样化数据集时，同时考虑多个阈值的加速度率分析以及各种影响因素的分析还存在空白。本分析将填补这一研究空白。该分析使用了第二战略公路研究计划自然驾驶研究（SHRP2 NDS）的数据。使用基于负二项分布的广义线性混合效应模型对加速时段率的发生进行建模。道路速度类别、驾驶员年龄、性别、车辆类型和位置被用作固定效应，驾驶员标识符被用作随机效应。然后计算发病率比以比较每个固定效应的子类别。道路速度类别对所有幅度的纵向和横向加速度的影响最大。随着道路速度类别的增加，加速时段率持续下降。差异取决于阈值，可达三个数量级。驾驶员年龄是另一个重要因素，纵向和横向加速时段率有明显趋势。年轻和年长的驾驶员经历更高的纵向加速度和减速。然而，横向加速度的速率随着年龄的增长而持续下降。车辆类型对苛刻的加速时段率也有显著影响，小型货车的加速时段率始终较低。
