Recent advances in the network-level traffic flow modelling provide an efficient tool for analyzing traffic performance of large-scale networks. A relationship between density and flow at the network level is developed and widely studied, namely the macroscopic fundamental diagram (MFD). Nevertheless, few empirical studies have been dedicated on the empirical evidence on the properties of the MFD for multiple modes of transport and to the best knowledge not yet at the scale of a megacity. This work combines rich, but incomplete data from multiple sources to investigate the vehicle and passenger MFDs for cars and buses in the road network of Shenzhen. A novel algorithm is proposed for partitioning bimodal network considering the homogeneous distribution of link-level car speeds and bus speeds.

Furthermore, this paper sheds light on the passenger MFD for mixed car-bus networks. We propose an algorithm to estimate alighting passenger flow and passenger density on bus, by fusing smart card data (i.e. records for boarding passengers) and bus GPS data. We analyze the complexities of passenger flow and the impact of weather on traffic demand and bus occupancy. The results provide an empirical knowledge on multimodal traffic performance with respect to passenger flow. The existence of double hysteresis loops in bus passenger MFD is observed and the causes are explained by considering the influence of service operational features. The three-dimensional vehicle and passenger MFDs are also presented for revealing the complex dynamics characteristics of bimodal road network.

网络级流量模型的最新进展为分析大型网络的流量性能提供了一种有效的工具。在网络级别上密度和流量之间的关系得到了开发和广泛研究，即宏观基本图（MFD）。然而，很少有关于MFD对于多种运输方式的性质以及尚未达到超大城市规模的最佳知识的经验证据的经验研究。这项工作结合了来自多个来源的丰富但不完整的数据，以调查深圳道路网中汽车和公共汽车的车辆和乘客MFD。提出了一种基于链路级车速和公交车速度均匀分布的双峰网络划分算法。

此外，本文为混合型汽车-公共汽车网络的乘客MFD提供了启示。我们提出了一种算法，通过融合智能卡数据（即登机乘客的记录）和公交GPS数据来估算公交车上的客流和乘客密度。我们分析了客流的复杂性以及天气对交通需求和公交车占用的影响。结果提供了关于客流的多式联运性能的经验知识。观察了公交乘员MFD中双磁滞回线的存在，并通过考虑服务运行特性的影响来解释其原因。还提出了三维车辆和乘客MFD，以揭示双峰路网的复杂动力学特征。