具有相同驾驶员的微观确定性交通模型的分类与统一
Classification and Unification of the Microscopic Deterministic Traffic Models with Identical Drivers
摘要：
我们表明，所有现有的确定性微观交通模型与相同的驱动程序（包括两个阶段和三相模型）可以理解为特殊情况下，从一个主模型周围的扩展定义良好的基态。这使得两个流量模型可以以明确定义的方式进行比较。三相模型的特点是在一定的密度范围内的膨胀的领先订单消失，并作为一个例子，流行的智能驱动程序模型（IDM）被证明是等效的广义最优速度（OV）模型。我们还探索了广义OV模型的各种解决方案，这些解决方案对于理解人类驾驶行为和自动驾驶车辆的算法都很重要。
英文摘要：
We show that all existing deterministic microscopic traffic models with identical drivers (including both two-phase and three-phase models) can be understood as special cases from a master model by expansion around well-defined ground states. This allows two traffic models to be compared in a well-defined way. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver models (IDM) is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
