论文标题
参数回归模型的比较研究，以检测流量基本图中的断点
A Comparative Study of Parametric Regression Models to Detect Breakpoint in Traffic Fundamental Diagram
论文作者
论文摘要
速度阈值是分解和容量分布分析的关键参数，因为它定义了自由流动和拥挤的制度之间的边界。但是，关于确定检测分解事件的断点值的方法的文献是有限的。大多数现有研究都取决于视觉观察或预定义阈值的使用。考虑到与现场数据相关的变化，这些方法可能并不可靠。因此，这项研究比较了两种数据驱动方法的性能，即逻辑函数（LGF）和两级模型，用于建立流量流量变量的断点。使用城市高速公路交通数据对这两种型号进行了校准。模型的性能结果表明，通过较少的计算工作，LGF的预测准确性比两场模型略好。尽管两场模型的性能相对较低，但对于识别过渡状态可能是有用的。
A speed threshold is a crucial parameter in breakdown and capacity distribution analysis as it defines the boundary between free-flow and congested regimes. However, literature on approaches to establishing the breakpoint value for detecting breakdown events is limited. Most of existing studies rely on the use of either visual observation or predefined thresholds. These approaches may not be reliable considering the variations associated with field data. Thus, this study compared the performance of two data-driven methods, that is, logistic function (LGF) and two-regime models, used to establish the breakpoint from traffic flow variables. The two models were calibrated using urban freeway traffic data. The models'performance results revealed that with less computation efforts, the LGF has slightly better prediction accuracy than the two-regime model. Although the two-regime model had relatively lower performance, it can be useful in identifying the transitional state.
