p-value and mean absolute error (MAE).

Platoon based traffic flow models form the underlying theoretical framework in traffic simulation tools. They are essentially important in facilitating efficient performance calculation and evaluation in urban traffic networks. For this purpose, a new platoon-based macroscopic model called the LWR-IM has been developed in [1]. Preliminary analytical validation conducted previously has proven the feasibility of the model. In this paper, the LWR-IM is further enhanced with algorithms that describe platoon interactions in urban arterials. The LWR-IM and the proposed platoon interaction algorithms are implemented in the real-world class I and class II urban arterials. Another purpose of the work is to perform quantitative validation to investigate the validity and ability of the LWR-IM and its underlying algorithms to describe platoon interactions and simulate performance indices that closely resemble the real traffic situations. The quantitative validation of the LWR-IM is achieved by performing a two-sampled t-test on queues simulated by the LWR-IM and real queues observed at these real-world locations. The results reveal insignificant differences of simulated queues with real queues where the p-values produced concluded that the null hypothesis cannot be rejected. Thus, the quantitative validation further proved the validity of the LWR-IM and the embedded platoon interactions algorithm for the intended purpose.

基于车队（platoon）的交通流模型是交通仿真工具的底层理论框架，其可助力城市交通网络高效开展性能计算与评估工作。为此，文献[1]中提出了一种名为LWR-IM的新型车队宏观交通流模型。此前开展的初步分析验证已证实该模型具备可行性。本文针对LWR-IM进行了进一步优化，新增了可描述城市主干道上车队交互行为的算法，并将LWR-IM与所提出的车队交互算法部署于真实的一类、二类城市主干道场景中。本研究的另一项目标是开展定量验证，以检验LWR-IM及其内嵌算法在描述车队交互行为、模拟贴近真实交通状况的性能指标方面的有效性与适配能力。LWR-IM的定量验证通过对模型模拟得到的排队队列与真实场景中观测得到的实际排队队列进行双样本t检验完成。检验结果显示模拟队列与实际队列之间无显著差异：所得p值表明无法拒绝原假设。因此，本次定量验证进一步证实了LWR-IM及其内嵌车队交互算法在预期用途下的有效性。