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ICAT: An Indoor Connected and Autonomous Testbed for Vehicle Computing

Zhaofeng Tian, William He, Boyang Tian, Ren Zhong, Erfan Foorginejad, Weisong Shi

TL;DR

The Indoor Connected Autonomous Testbed (ICAT), a platform that not only tackles the unique challenges of indoor autonomous driving but also innovates vehicle computing and V2X communication, is introduced.

Abstract

Indoor autonomous driving testbeds have emerged to complement expensive outdoor testbeds and virtual simulations, offering scalable and cost-effective solutions for research in navigation, traffic optimization, and swarm intelligence. However, they often lack the robust sensing and computing infrastructure for advanced research. Addressing these limitations, we introduce the Indoor Connected Autonomous Testbed (ICAT), a platform that not only tackles the unique challenges of indoor autonomous driving but also innovates vehicle computing and V2X communication. Moreover, ICAT leverages digital twins through CARLA and SUMO simulations, facilitating both centralized and decentralized autonomy deployments.

ICAT: An Indoor Connected and Autonomous Testbed for Vehicle Computing

TL;DR

The Indoor Connected Autonomous Testbed (ICAT), a platform that not only tackles the unique challenges of indoor autonomous driving but also innovates vehicle computing and V2X communication, is introduced.

Abstract

Indoor autonomous driving testbeds have emerged to complement expensive outdoor testbeds and virtual simulations, offering scalable and cost-effective solutions for research in navigation, traffic optimization, and swarm intelligence. However, they often lack the robust sensing and computing infrastructure for advanced research. Addressing these limitations, we introduce the Indoor Connected Autonomous Testbed (ICAT), a platform that not only tackles the unique challenges of indoor autonomous driving but also innovates vehicle computing and V2X communication. Moreover, ICAT leverages digital twins through CARLA and SUMO simulations, facilitating both centralized and decentralized autonomy deployments.
Paper Structure (16 sections, 6 figures, 1 table, 1 algorithm)

This paper contains 16 sections, 6 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Motivation and Challenge
  3. Related Work
  4. ICAT Design
  5. Digital Twin
  6. Infrastructure and V2X
  7. Localization
  8. Centralized Traffic Management System
  9. Decentralized Autonomous Driving
  10. Vehicle Computing and Multi-user Management
  11. HydraT Platform and Auto-recharge
  12. Case Studies
  13. Traffic Management System
  14. Federated Machine Learning
  15. Discussion and Future Work
  16. ...and 1 more sections

Figures (6)

  • Figure 1: Panoptic view of ICAT platform in real world. ICAT is 6 by 5 meters in size, and 10 intelligent robots are used in ICAT now for autonomous driving studies. Traffic lights and signs are now integrated seamlessly with ICAT and enable interactions with traffic agents
  • Figure 2: Digital twin system of ICAT. (a) ICAT's map is designed within RoadRunner roadrunner, which is a 3D interactive autonomous driving system builder. (b) The designed map then can be seamlessly imported into CARLA simulations. (c) SUMO simulations are also enabled with the ICAT road system.
  • Figure 3: ICAT traffic management system testing in a Python simulation, where simulated 10 traffic agents could be controlled by a centralized traffic management algorithm. The planned trajectories for different robots are marked in different colors.
  • Figure 4: Graph topology for ICAT traffic system, consisting of nodes and edges that a pair of nodes is connected with either a straight line or a curve. Waypoints are discretized with a fixed distance as an attribute of the edge.
  • Figure 5: Our designed HydraT platform, is equipped with an advanced Lidar-camera sensing system and empowered with up-to-date navigation software.
  • ...and 1 more figures