In the near future, transportation systems modelers and planners will likely be challenged by more complex scenarios. This is due to the different types of vehicles that include different (i) powertrains (conventional, hybrid, electric, etc.), (ii) ownerships (privately-owned vs. shared vehicles), and (iii) levels of automation (from human-driven to fully autonomous). All these different vehicle types compete for the same arcs and jointly participate to congestion. Thus, existing methods for travel demand assignment to a transportation network, the main tools for transportation systems analysis to support transportation project assessment and evaluation, need to be extended to cope with mixed traffic. In this paper, deterministic process models for day-to-day dynamic multivehicle assignment are presented, including fixed-point models for equilibrium assignment as a special case. Vehicle types may be distinguished with respect to several parameters, such as flow equivalence coefficient, occupancy factor, cost equivalence coefficient, and behavioral parameters. Results of an application to a toy network are also discussed showing that advanced vehicles (AVs) may or may not have a positive effect of equilibrium stability.

中文翻译：

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日常动态多车辆分配：确定性过程模型

在不久的将来，运输系统建模人员和计划人员可能会面临更复杂的场景的挑战。这是由于车辆类型不同，其中包括（i）动力总成（常规，混合动力，电动等），（ii）所有权（私有车辆与共享车辆）以及（iii）自动化水平（来自人为驱动到完全自主）。所有这些不同类型的车辆争夺相同的弧度，并共同参与交通拥堵。因此，需要扩展现有的将交通需求分配给交通网络的方法，将其作为支持交通项目评估和评估的交通系统分析的主要工具，以应对混合交通。本文提出了用于日常动态多车辆分配的确定性过程模型，包括用于平衡分配的定点模型（作为特例）。可以根据几个参数来区分车辆类型，例如流量当量系数，占用系数，成本当量系数和行为参数。还讨论了对玩具网络的应用结果，表明先进的车辆（AV）可能会或可能不会对平衡稳定性产生积极影响。