Parallel Closed-Loop Connected Vehicle Simulator for Large-Scale Transportation Network Management: Challenges, Issues, and Solution Approaches

TL;DR

This paper introduces a parallel, large-scale transportation network simulator integrating real-time traffic data and hardware-in-the-loop simulation, addressing challenges like scalability, synchronization, and data management for smart city applications.

Contribution

It proposes a novel integrated distributed connected vehicle simulator (IDCVS) with hybrid parallelism and real-time data integration, advancing large-scale urban traffic simulation capabilities.

Findings

Developed a conceptual model combining SUMO and OMNET++ for real-time traffic simulation.

Addressed key challenges in scalability, synchronization, and data handling for large-scale simulations.

Highlighted the importance of multi-source sensor data integration for accurate traffic modeling.

Abstract

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.