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ColosSUMO: Evaluating Cooperative Driving Applications with Colosseum

Gabriele Gemmi, Pedram Johari, Paolo Casari, Michele Polese, Tommaso Melodia, Michele Segata

TL;DR

ColosSUMO addresses the challenge of realistic CCAM evaluation by bridging Colosseum's hardware-in-the-loop wireless emulation with SUMO mobility simulation. It enables running CCAM applications over real network stacks (e.g., 5G) with SDR-based channel emulation, coordinating mobility and networking via MQTT. The paper demonstrates a three-vehicle platoon experiment showing that wireless conditions (e.g., RSRP, BLER, MCS) drive end-to-end delays and trigger fallback between cooperative and non-cooperative control, impacting inter-vehicle spacing. This approach provides a scalable, accessible platform for reproducible CCAM studies and cross-technology comparisons, with open-source release planned.

Abstract

The quest for safer and more efficient transportation through cooperative, connected and automated mobility (CCAM) calls for realistic performance analysis tools, especially with respect to wireless communications. While the simulation of existing and emerging communication technologies is an option, the most realistic results can be obtained by employing real hardware, as done for example in field operational tests (FOTs). For CCAM, however, performing FOTs requires vehicles, which are generally expensive. and performing such tests can be very demanding in terms of manpower, let alone considering safety issues. Mobility simulation with hardware-in-the-loop (HIL) serves as a middle ground, but current solutions lack flexibility and reconfigurability. This work thus proposes ColosSUMO as a way to couple Colosseum, the world's largest wireless network emulator, with the SUMO mobility simulator, showing its design concept, how it can be exploited to simulate realistic vehicular environments, and its flexibility in terms of communication technologies.

ColosSUMO: Evaluating Cooperative Driving Applications with Colosseum

TL;DR

ColosSUMO addresses the challenge of realistic CCAM evaluation by bridging Colosseum's hardware-in-the-loop wireless emulation with SUMO mobility simulation. It enables running CCAM applications over real network stacks (e.g., 5G) with SDR-based channel emulation, coordinating mobility and networking via MQTT. The paper demonstrates a three-vehicle platoon experiment showing that wireless conditions (e.g., RSRP, BLER, MCS) drive end-to-end delays and trigger fallback between cooperative and non-cooperative control, impacting inter-vehicle spacing. This approach provides a scalable, accessible platform for reproducible CCAM studies and cross-technology comparisons, with open-source release planned.

Abstract

The quest for safer and more efficient transportation through cooperative, connected and automated mobility (CCAM) calls for realistic performance analysis tools, especially with respect to wireless communications. While the simulation of existing and emerging communication technologies is an option, the most realistic results can be obtained by employing real hardware, as done for example in field operational tests (FOTs). For CCAM, however, performing FOTs requires vehicles, which are generally expensive. and performing such tests can be very demanding in terms of manpower, let alone considering safety issues. Mobility simulation with hardware-in-the-loop (HIL) serves as a middle ground, but current solutions lack flexibility and reconfigurability. This work thus proposes ColosSUMO as a way to couple Colosseum, the world's largest wireless network emulator, with the SUMO mobility simulator, showing its design concept, how it can be exploited to simulate realistic vehicular environments, and its flexibility in terms of communication technologies.
Paper Structure (5 sections, 5 figures)

This paper contains 5 sections, 5 figures.

Table of Contents

  1. Introduction and Related Work
  2. Architecture
  3. Validation of the HIL emulator.
  4. Metrics and Results
  5. Conclusions and Future Work

Figures (5)

  • Figure 1: ColosSUMO architecture. Vehicular components are shown in green, while the wireless communication components are in yellow.
  • Figure 2: Map of the scenario showing the path of the vehicles, their start position, and the location of the gNB. Image courtesy OpenStreetMap.
  • Figure 3: State of the wireless channel between the three vehicles and the gNB.
  • Figure 4: Average MCS and average end-to-end delay.
  • Figure 5: Distance between the vehicles.