This paper shows how traffic heterogeneity, and the way it is encoded into a model, drastically affects a model ability to reproduce observed traffic. Being heterogeneity a major source of uncertainty, to correctly frame the proposed validation methodology we have first reviewed and adapted cross-disciplinary theoretical concepts about uncertainty modelling to traffic simulation. A number of open issues, including error compensation and model overfitting, has been interpreted and clarified through the proposed framework. A two-level probabilistic approach has been applied to run stochastic simulations of three NGSIM I-80 traffic scenarios, and quantitatively infer the impact of heterogeneity. According to this approach, both the car-following and the lane-changing models of each vehicle have been calibrated against observed trajectories. Based on the estimated parameters distributions, different models of heterogeneity have been quantitatively validated against macroscopic traffic patterns. Being traffic a collective phenomenon emerging from microscopic interactions, even models calibrated on microscopic trajectories need to be quantitatively validated on macroscopic traffic patterns too. Among other results, normal distributions of the model parameters, which are customarily applied in traffic simulation practice, have been found unable to reproduce the observed congestion patterns. Parameters correlation, being claimed as highly influential in previous works, is responsible for a model overfitting in traffic scenarios with low congestion. In the end, it has been demonstrated that a thorough characterization of parameters heterogeneity cannot be left out in traffic simulation, if an ersatz representation of traffic is to be avoided.

本文展示了流量异质性及其如何被编码为模型的方式，极大地影响了模型重现观察到的流量的能力。由于异质性是不确定性的主要来源，为了正确地提出建议的验证方法，我们首先回顾了关于不确定性建模的跨学科理论概念，并将其适用于交通仿真。通过提议的框架已经解释和阐明了许多未解决的问题，包括误差补偿和模型过度拟合。已应用两级概率方法对三种NGSIM I-80交通场景进行随机模拟，并定量推断异质性的影响。根据这种方法，已经针对观察到的轨迹校准了每辆车的跟车模型和变道模型。基于估计的参数分布，已针对宏观交通模式对不同的异构模型进行了定量验证。由于交通是微观互动产生的一种集体现象，因此即使在微观轨迹上校准的模型也需要在宏观交通模式上进行定量验证。在其他结果中，发现通常在交通模拟实践中应用的模型参数的正态分布无法重现观察到的拥塞模式。参数关联在以前的工作中被认为具有很高的影响力，这是模型在交通拥堵程度低的情况下过拟合的原因。最后，我们证明了在流量仿真中不能遗漏对参数异质性的全面描述，