Cooperative Driving Automation (CDA) Small-Scale Industry Prototype

occlusion, complex merging, or identifying pedestrians hidden behind buildings at corners, and vehicle sensors alone cannot adequately resolve these issues. Prior USDOT-supported research projects have successfully demonstrated the technical proof-of-concept at technology readiness levels (TRL) of 3-5 for CDA applications in laboratory and closed environments. However, most new vehicles are not equipped with CDA capabilities and Original Equipment Manufacturers (OEMs) remain reluctant to integrate these technologies into production lines due to a lack of consumer awareness and unclear regulatory, policy, and institutional frameworks. This acquisition seeks to build on foundational CDA research by bridging the gap between research concepts and commercial viability. There is a critical need to develop and test pre-production, industry-led prototypes at a TRL of 6-7, to validate that the data shared between vehicles and roadside infrastructure is accurate, secure, and reliable enough to support functional safety. By demonstrating CDA technologies in operational conditions, researchers will gain a better understanding of cooperative systems and if they are more valuable in terms of improving roadway safety, than standalone automation or vehicle-to-everything (V2X) technologies alone. PURPOSE: The purpose of this requirement is to demonstrate industry-led CDA prototypes in controlled and real-world conditions in order to generate data-driven insights that will support the development of a national strategy to deploy CDA across rural, suburban, and urban roadway systems. This effort prioritizes industry-ready CDA technology for use cases with clear safety and/or mobility benefit potential, specifically focusing on: (1) Work Zone Management, (2) Traffic Incident Management, (3) Cooperative Perception, and/or (4) Emergency/Transit Vehicle Awareness. Contractors will first validate the prototype's interoperability, functional safety, and cybersecurity in a relevant, controlled testbed environment. Following successful controlled testing, the effort will progress into a small scale real-world demonstration on public roads with mixed traffic to validate operational readiness and generate data-driven insights.