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

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. W Pre-print (Authors' Version) Communication (DSRC) technology. Automakers and technology developers like Google, Ford, and General Motors etc. are working to improve the controllability features of autonomous or semi-autonomous vehicles. While self-driving cars can potentially reduce the stress of navigating through congested traffic, CVs can optimize the traffic flow across an entire transportation network through the exchange of information among vehicles and infrastructure. CV applications use information obtained through V2X communications to assist drivers in avoiding congestion, reducing vehicle stops, choosing the best route, and optimizing fuel efficiency. Hence, CV-based emerging Intelligent Transportation Systems (ITS) applications can result in transformative changes to the overall surface transportation system.To accurately simulate ITS applications on a scenario involving connected vehicles, it is necessary to integrate a full-fledged transportation simulator with a wireless network simulator, resulting in the need for a closed-loop simulator. This kind of closed-loop simulator requires a tight synchronization between two stand-alone simulation modules: a transportation module and a communication module. The transportation module is responsible for the modeling of vehicle mobility applications including traffic routing, ca...

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