ABSTRACT This research explores how road grade impacts the operations of light-duty vehicles and heavy-duty express buses on freeways. The Bayesian Hierarchical Model (BHM) used in this research employs three variable levels: trace-level (for individual trip effects), vehicle-level (for individual vehicle effects), and fleet-level (for overall sample effect). The vehicle level parameters represent the effects of specific vehicle performance characteristics and drivers’ behaviors on grade (and the hidden effects of driver behavior associated with the vehicle) and display random impact heterogeneity across vehicles and drivers. Fleet level parameters capture operations across the entire sample set. First-order autoregressive covariance matrices represent auto-correlation of speed and acceleration within the time series of each trace. Significant heterogeneity of road grade impact is observed across vehicles. The study provides a reference to microscopic speed and acceleration choices model considering the impact heterogeneity of road grade across vehicles or drivers on the hilly freeway.

中文翻译：

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估计道路坡度对高速公路车速和加速度影响的贝叶斯方法

摘要 本研究探讨了道路坡度如何影响高速公路上轻型车辆和重型快速巴士的运行。本研究中使用的贝叶斯分层模型 (BHM) 使用三个变量级别：跟踪级别（针对个人旅行效果）、车辆级别（针对个人车辆效果）和车队级别（针对整体样本效果）。车辆级别参数代表特定车辆性能特征和驾驶员行为对等级的影响（以及与车辆相关的驾驶员行为的隐藏影响），并显示车辆和驾驶员之间的随机影响异质性。车队级参数捕获整个样本集的操作。一阶自回归协方差矩阵表示每个轨迹的时间序列内速度和加速度的自相关。在车辆之间观察到道路坡度影响的显着异质性。该研究为考虑道路坡度对丘陵高速公路上车辆或驾驶员的影响异质性的微观速度和加速度选择模型提供了参考。