面向大规模交通网络管理的并行闭环互联车辆模拟器：挑战、问题和解决方案
Parallel Closed-Loop Connected Vehicle Simulator for Large-Scale Transportation Network Management: Challenges, Issues, and Solution Approaches
摘要：
城市交通网络的规模和复杂性的增加大大增加了车辆网络仿真的执行时间和资源需求，超过了顺序仿真器的能力。从智慧城市的角度来看，对并行和分布式仿真环境的需求是不可避免的，特别是当整个城市范围的信息系统预计将与众多服务和ITS应用集成时。在本文中，我们提出了一个概念模型的集成分布式连接车辆模拟器（IDCVS），可以模拟实时交通在一个大的都会区，结合硬件在环仿真与闭环耦合的SUMO和OMNET++。我们还讨论了挑战，问题和解决方案，实现这样一个并行的闭环交通网络模拟器，通过解决交通网络分区问题，同步和可扩展性问题。设想的集成仿真工具的一个独特的功能是，它利用通过多个道路传感器DSRC车载单元，磁力计，环路检测器和视频检测器收集的车辆轨迹。该模型的另一个主要特点是在交通和通信仿真平台的混合并行。我们确定的挑战和问题，在IDCVS纳入这种多级并行。我们还讨论了集成硬件在环仿真的方法，解决涉及预处理传感器数据，过滤和外推丢失的数据，管理大型实时交通数据，并处理不同的数据格式的步骤。
英文摘要：
The augmented scale and complexity of urban transportation networks have significantly increased the execution time and resource requirements of vehicular network simulations, exceeding the capabilities of sequential simulators. The need for a parallel and distributed simulation environment is inevitable from a smart city perspective, especially when the entire city-wide information system is expected to be integrated with numerous services and ITS applications. In this paper, we present a conceptual model of an Integrated Distributed Connected Vehicle Simulator (IDCVS) that can emulate real-time traffic in a large metro area by incorporating hardware-in-the-loop simulation together with the closed-loop coupling of SUMO and OMNET++. We also discuss the challenges, issues, and solution approaches for implementing such a parallel closed-loop transportation network simulator by addressing transportation network partitioning problems, synchronization, and scalability issues. One unique feature of the envisioned integrated simulation tool is that it utilizes the vehicle traces collected through multiple roadway sensors-DSRC onboard unit, magnetometer, loop detector, and video detector. Another major feature of the proposed model is the incorporation of hybrid parallelism in both transportation and communication simulation platforms. We identify the challenges and issues involved in IDCVS to incorporate this multi-level parallelism. We also discuss the approaches for integrating hardware-in-the-loop simulation, addressing the steps involved in preprocessing sensor data, filtering, and extrapolating missing data, managing large real-time traffic data, and handling different data formats.
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。
