Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual world with various traffic entities (e.g., vehicles and pedestrians). Typically, the movements of these entities in the simulation are governed by some pre-defined algorithms (e.g., car-following models and lane-changing models). Modelers may develop customized algorithms through an application programming interface (API). In comparison to the human-controlled vehicles, however, any algorithm will fall short. Other than the configuration of some simplified behavioral parameters (e.g., reaction time), most of the existing MTS models have limited human-in-the-loop simulation abilities to capture the interactions among simulated entities. Besides, most existing MTS models do not provide a realistic virtual environment that enables high-fidelity simulations of the driver behavior in response to various driving conditions, such as road and weather conditions. This paper aims to develop a framework for improving MTS models and extending their capabilities by incorporating distributed vehicles controlled by human-in-the-loop with virtual reality (VR) technologies. This framework supports not only multiple/many users from geographically distributed locations but also interactive visualizations with VR devices from the perspective of a driver and other users (e.g., pedestrians). Data collected from the user-controlled vehicles can be used to calibrate different algorithms like car following, lane changing, etc., or to explore the virtual world from different perspectives for design investigation by potential stakeholders. This paper describes the overall framework, the significant challenges in the proposed approach, and our solutions to these challenges.

微观交通仿真（MTS）是在虚拟世界中使用各种交通实体（例如，车辆和行人）对现实世界中交通运动的仿真。通常，这些实体在模拟中的运动受某些预定义算法（例如，跟车模型和变道模型）控制。建模人员可以通过应用程序编程接口（API）开发定制的算法。但是，与人为控制的车辆相比，任何算法都无法实现。除了某些简化的行为参数（例如，反应时间）的配置之外，大多数现有的MTS模型具有有限的“在环仿真”能力，无法捕获仿真实体之间的交互。除了，大多数现有的MTS模型都没有提供现实的虚拟环境，无法对驾驶员的行为进行高保真模拟，以响应各种驾驶条件，例如道路和天气条件。本文旨在通过将由环人控制的分布式车辆与虚拟现实（VR）技术相结合，开发出一种改进MTS模型并扩展其功能的框架。该框架不仅支持来自地理位置分散的多个/许多用户，而且还从驾驶员和其他用户（例如行人）的角度支持与VR设备的交互式可视化。从用户控制的车辆收集的数据可用于校准不同的算法，例如跟踪车辆，改变车道等，或从不同的角度探索虚拟世界，以供潜在的利益相关者进行设计调查。本文介绍了总体框架，拟议方法中的重大挑战以及我们对这些挑战的解决方案。