Simulation to Reality: Testbeds and Architectures for Connected and Automated Vehicles

2025-05-06

AI Summary

This study addresses the challenge of transferring connected and autonomous vehicle (CAV) software frameworks across simulation, small-scale experimentation, and full-scale real-world testing. To bridge this gap, we systematically establish the first comprehensive evaluation framework covering all testing phases. Our methodology integrates architectural analysis of CAV software frameworks, toolchain benchmarking, multi-level case validation using ROS2, Autoware, and CARLA, and a systematic literature review—thereby identifying cross-phase adaptation bottlenecks in perception, planning, and control modules. As a key contribution, we propose a novel CAV Software Framework Capability Assessment Matrix. This matrix explicitly characterizes six core technical bottlenecks and three categories of critical toolchain requirements. It provides actionable architectural guidance to enhance real-time performance, communication reliability, and computational resource efficiency—ultimately supporting the safe, robust, and scalable development and deployment of CAV systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Computer Vision: Vision for Robotics & Autonomous Driving

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Consent frameworks and practices on the web

Abstract

Ensuring the safe and efficient operation of CAVs relies heavily on the software framework used. A software framework needs to ensure real-time properties, reliable communication, and efficient resource utilization. Furthermore, a software framework needs to enable seamless transition between testing stages, from simulation to small-scale to full-scale experiments. In this paper, we survey prominent software frameworks used for in-vehicle and inter-vehicle communication in CAVs. We analyze these frameworks regarding opportunities and challenges, such as their real-time properties and transitioning capabilities. Additionally, we delve into the tooling requirements necessary for addressing the associated challenges. We illustrate the practical implications of these challenges through case studies focusing on critical areas such as perception, motion planning, and control. Furthermore, we identify research gaps in the field, highlighting areas where further investigation is needed to advance the development and deployment of safe and efficient CAV systems.

Problem

• Ensuring safe and efficient CAV operation via software frameworks
• Enabling seamless transition between simulation and real-world testing stages
• Addressing challenges in real-time properties and communication for CAVs

Innovation

• Real-time software framework for CAVs
• Seamless simulation to full-scale transition
• Tooling for perception and control challenges