Self-organized criticality (SOC) is a celebrated paradigm from the 90’s for understanding dynamical systems naturally driven to its critical point, where the power-law dynamics taking place make predictions practically impossible, such as in stock prices, earthquakes, pandemics and many other problems in science related to phase transitions. Shortly thereafter, it was realized that traffic flow might be in the SOC category, implying that conventional traffic management strategies seeking to maximize the local flows can become detrimental. This paper shows that the Kinematic Wave model with triangular fundamental diagram, and many other related traffic models, indeed exhibit SOC, thanks in part to the fractal nature of traffic exposed here on the one hand, and our need to get to our destinations as soon as possible, on the other hand.Important implications for congestion management of traffic near the critical region are discussed, such as: (i) Jam sizes obey a power-law distribution with exponent 1/2, implying that both its mean and variance become ill-defined and therefore impossible to estimate. (ii) Traffic in the critical region is chaotic in the sense that predictions becomes extremely sensitive to initial conditions. (iii) However, aggregate measures of performance such as delays and average speeds are not heavy tailed, and can be characterized exactly by different scalings of the Airy distribution, (iv) Traffic state time–space “heat maps” are self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams. This fractal nature of traffic flow calls for analysis methods currently not used in our field.

自组织临界性 (SOC) 是 90 年代的一个著名范例，用于理解自然驱动到其临界点的动力系统，其中发生的幂律动力学使得预测几乎不可能，例如股票价格、地震、流行病和许多其他与相变有关的科学问题。此后不久，人们意识到交通流量可能属于 SOC 类别，这意味着寻求最大化本地流量的传统交通管理策略可能变得有害。本文表明，具有三角基本图的运动波模型和许多其他相关交通模型确实表现出 SOC，一方面要归功于这里暴露的交通的分形性质，以及我们需要尽快到达目的地另一方面，尽可能。讨论了对关键区域附近交通拥堵管理的重要影响，例如：(i) 拥堵大小服从指数为 1/2 的幂律分布，这意味着其均值和方差都变得不确定，因此无法估计. (ii) 在预测对初始条件变得极其敏感的意义上，关键区域的交通是混乱的。(iii) 然而，诸如延误和平均速度之类的综合性能指标并不是重尾的，并且可以通过艾里分布的不同尺度来准确表征，(iv) 交通状态时空“热图”是自仿射分形其中基本单元是一个三角形，呈基本图的形状，包含 3 种交通状态：空隙、通行能力和拥堵。