Cooperative Automation Research: CARMA Proof-of-Concept TSMO Use Case Testing: CARMA Cooperative Perception Concept of Operations

Lou, Yingyan; Ghiasi, Amir; Jannat, Mafruhatul; Racha, Sujith; Hale, David; Goforth, Wade; Bujanovic, Pavle · 2022 · ROSA P / United States. Federal Highway Administration

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Summary

This document presents a Concept of Operations (ConOps) for Cooperative Perception (CP) within the Federal Highway Administration’s (FHWA) Cooperative Driving Automation (CDA) Program, formerly known as the CARMA Program. The research addresses the need to enhance the safety, traffic throughput, and energy efficiency of transportation networks by enabling vehicles and infrastructure to share locally perceived data. While automated driving systems typically rely on onboard sensors, CP leverages vehicle-to-everything (V2X) communications to share perception of road objects, such as vulnerable road users (VRUs) or static obstacles, with other entities. This capability is particularly critical in mixed-traffic environments where not all road users are equipped with communication technology, or when line-of-sight is obstructed by geometry, weather, or large vehicles. The document serves as the eighth in a series of nine reports focused on transportation systems management and operations use cases, aiming to define testable scenarios and system requirements for CP integration into the open-source CARMA Ecosystem. The methodology involves a comprehensive review of current technical practices, stakeholder needs, and literature on CP, including object detection, communication protocols, cybersecurity, and data fusion algorithms. The authors define the technological framework for CP within the CARMA Ecosystem, detailing communication protocols, data fusion algorithms, and functional performance metrics. The report outlines specific operational needs and infrastructure configurations required to support CP. It further develops fourteen distinct operational scenarios categorized into four applications: interacting with VRUs (e.g., crossings at controlled and nondesignated areas), collision avoidance (e.g., wrong-way driving), conflict avoidance and cooperative driving (e.g., intersections and overtaking), and general enhancement of situational awareness (e.g., adverse weather or work zones). These scenarios illustrate how CP improves situational awareness through vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications. The findings establish a structured operational concept for CP, identifying key benefits such as improved perception performance for automated vehicles and CARMA Streets, which enables more effective safety and mobility applications. The document specifies functional requirements and performance metrics for traffic operations, vehicle behavior, and communication reliability. It also identifies potential limitations, including communication congestion, cybersecurity threats like falsified perception data, and challenges in data fusion when sensor fidelities differ between entities. The report proposes a system validation plan involving both simulation testing and field testing to verify the proposed concepts. The significance of this work lies in its contribution to the market readiness and deployment of cooperative driving automation technologies. By defining a clear ConOps for CP, the FHWA provides stakeholders—including system developers, infrastructure owners, and researchers—with a standardized framework for developing and implementing CP features. This facilitates the transition from standalone automated driving to cooperative strategies that leverage infrastructure, ultimately enhancing the overall safety and efficiency of the transportation network. The document supports the ongoing evolution of the CARMA Ecosystem, particularly the CARMA3 platform, which integrates automated driving systems with cooperative automation capabilities.

Key finding

The document establishes a comprehensive concept of operations for CARMA Cooperative Perception, defining its technical framework, functional requirements, and operational scenarios to enhance situational awareness and safety in cooperative driving automation.

Methodology

review

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Topics

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• v2x connected vehicle
• situational awareness

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• Methodological Resource: dataset resource