English

A Survey on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms

Robotics 2024-11-22 v2 Multiagent Systems

Abstract

Connected and automated vehicles and robot swarms hold transformative potential for enhancing safety, efficiency, and sustainability in the transportation and manufacturing sectors. Extensive testing and validation of these technologies is crucial for their deployment in the real world. While simulations are essential for initial testing, they often have limitations in capturing the complex dynamics of real-world interactions. This limitation underscores the importance of small-scale testbeds. These testbeds provide a realistic, cost-effective, and controlled environment for testing and validating algorithms, acting as an essential intermediary between simulation and full-scale experiments. This work serves to facilitate researchers' efforts in identifying existing small-scale testbeds suitable for their experiments and provide insights for those who want to build their own. In addition, it delivers a comprehensive survey of the current landscape of these testbeds. We derive 62 characteristics of testbeds based on the well-known sense-plan-act paradigm and offer an online table comparing 23 small-scale testbeds based on these characteristics. The online table is hosted on our designated public webpage https://bassamlab.github.io/testbeds-survey, and we invite testbed creators and developers to contribute to it. We closely examine nine testbeds in this paper, demonstrating how the derived characteristics can be used to present testbeds. Furthermore, we discuss three ongoing challenges concerning small-scale testbeds that we identified, i.e., small-scale to full-scale transition, sustainability, and power and resource management.

Keywords

Cite

@article{arxiv.2408.14199,
  title  = {A Survey on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms},
  author = {Armin Mokhtarian and Jianye Xu and Patrick Scheffe and Maximilian Kloock and Simon Schäfer and Heeseung Bang and Viet-Anh Le and Sangeet Ulhas and Johannes Betz and Sean Wilson and Spring Berman and Liam Paull and Amanda Prorok and Bassam Alrifaee},
  journal= {arXiv preprint arXiv:2408.14199},
  year   = {2024}
}

Comments

16 pages, 11 figures, 1 table. This work was accepted by the IEEE Robotics & Automation Magazine