Digital Twin is an emerging technology that replicates real-world entities into a digital space. It has attracted increasing attention in the transportation field and many researchers are exploring its future applications in the development of Intelligent Transportation System (ITS) technologies. Connected vehicles (CVs) and pedestrians are among the major traffic participants in ITS. However, the usage of Digital Twin in research involving both CV and pedestrian remains largely unexplored. In this study, a Digital Twin framework for CV and pedestrian in-the-loop simulation is proposed. The proposed framework consists of the physical world, the digital world, and data transmission in between. The features for the entities (CV and pedestrian) that need digital twining are divided into external state and internal state, and the attributes in each state are described. We also demonstrate a sample architecture under the proposed Digital Twin framework, which is based on Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). A case study that investigates Vehicle-Pedestrian (V2P) warning system is conducted to validate the effectiveness of the presented architecture. The proposed framework is expected to provide guidance to the future Digital Twin research, and the architecture we build can serve as the testbed for further research and development of ITS applications on CV and pedestrians.

翻译：数字孪生是一种将现实世界实体复制到数字空间的新兴技术。该技术在交通领域日益受到关注，众多研究者正在探索其在智能交通系统（ITS）技术开发中的未来应用。网联车辆和行人是智能交通系统中的主要交通参与者，然而，数字孪生在同时涉及网联车辆与行人的研究中仍鲜有应用。本研究提出了一种面向网联车辆与行人在环仿真的数字孪生框架。该框架由物理世界、数字世界及二者间的数据传输构成。需进行数字孪生的实体（网联车辆与行人）特征被划分为外部状态与内部状态，并描述了各状态中的属性。我们还基于Carla-Sumo协同仿真与Cave自动虚拟环境（CAVE），展示了所提数字孪生框架下的示例架构。通过一项针对车-人（V2P）预警系统的案例研究，验证了该架构的有效性。所提框架有望为未来数字孪生研究提供指导，而所构建的架构可作为进一步研发面向网联车辆与行人的智能交通系统应用的测试平台。