Driver parameter values for Hanoi.

Continuous improvement in computing power allowed for an increase of the scales micro-traffic models can be used at. Among them, agent-based frameworks are now appropriate for studying ordinary traffic conditions at city-scale, but remain difficult to adapt, especially for non-computer scientists, to more specific application contexts (e.g., car accidents, evacuation following a natural disaster), that require integrating particular behaviors for the agents. In this paper, we present a built-in model integrated into the GAMA open-source modeling and simulation platform, allowing the modeler to easily define traffic simulations with a detailed representation of the driver’s operational behaviors. In particular, it allows modelling road infrastructures and traffic signals, change of lanes by driver agents and less normative traffic mixing car and motorbike as in some South East Asian countries. Moreover, the model allows to carry out city-level simulations with tens of thousands of driver agents. An experiment carried out shows that the model can accurately reproduce the traffic in Hanoi, Vietnam.计算算力的持续提升，使得微观交通模型的可用应用尺度得到拓展。其中，基于智能体（agent）的框架目前适用于城市规模的常规交通场景研究，但在适配更多特定应用场景时仍存在难度——尤其是对于非计算机领域研究者而言——例如交通事故、自然灾害后的人员疏散等需要为智能体集成特定行为的场景。本文提出了一款集成于GAMA开源建模与仿真平台的内置模型，可帮助建模者便捷定义交通仿真场景，并对驾驶员的操作行为进行精细化表征。具体而言，该模型可对道路基础设施、交通信号灯、驾驶员智能体的车道变更行为进行建模，还能复现部分东南亚国家中汽车与摩托车混行的非规范交通场景。此外，该模型支持搭载数万名驾驶员智能体开展城市级交通仿真。经实验验证，该模型可精准复现越南河内的交通运行状况。