Infrastructure Readiness for Electric, Connected and Automated Vehicles-Policies, Planning, and Pilot Testing on Infrastructure Readiness for Electrical, Connected, Automated, and Ridesharing Vehicles
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Summary
This report addresses the critical gap in roadway infrastructure readiness for the adoption of Electric, Connected, and Automated Vehicles (ECAVs). While ECAVs are expected to enhance transportation safety, efficiency, and environmental sustainability, current infrastructure lacks the necessary connectivity and architectural support. The study, conducted by the Center for Advanced Infrastructure and Transportation (CAIT) in cooperation with the New Jersey Department of Transportation, aims to evaluate existing Intelligent Transportation Systems (ITS) architectures, identify technological gaps, and propose a preliminary system architecture and testbed design for New Jersey. The methodology involves a comprehensive review of two primary ITS system architectures: the internationally driven ITS Station Architecture and the U.S.-based Connected Vehicle Reference Implementation Architecture (CVRIA). The authors analyze the strengths and limitations of these frameworks, noting that while the ITS Station Architecture provides detailed communication standards, CVRIA offers a broader scope focused on physical objects and stakeholder benefits. The report also evaluates advanced communication technologies, comparing Direct Short Range Communication (DSRC), millimeter wave (mmWave), and Cellular V2X (C-V2X) including 4G LTE and 5G. Additionally, the study outlines data requirements and physical infrastructure challenges, such as road marking recognition under varying conditions. To validate the proposed architecture, the researchers developed a digital simulation model for a roadway segment in New Brunswick, New Jersey, focusing on an Adaptive Signal Control (ASC) application. Key findings indicate that 5G V2X outperforms DSRC and mmWave in latency, bandwidth, and reliability, making it the most suitable technology for advanced use cases like platooning and remote driving. The report details specific application logic flows for adaptive signal control, electric charging management, in-vehicle signage, reduced speed zone warnings, and 3D map management. Simulation results from the New Brunswick case study demonstrate that connected vehicles utilizing Adaptive Signal Control significantly reduce average travel time and queue waiting times compared to legacy vehicles and connected vehicles without ASC. The study also identifies critical barriers, including the lack of deployed Roadside Units (RSUs) for DSRC and the need for standardized data exchange protocols. The significance of this work lies in providing a conceptual framework for transportation agencies to transition toward ECAV-ready infrastructure. By identifying gaps between current practices and best-in-class architectures, the report offers a roadmap for implementing connected roadway systems. The proposed preliminary testbed design and simulation evidence support the argument that infrastructure upgrades are essential to realize the full benefits of ECAVs. The findings underscore the necessity of integrating advanced communication technologies and standardized ITS architectures to manage congestion, improve safety, and support the operational needs of electric and automated vehicles.
Key finding
5G V2X technology outperforms DSRC and mmWave in all advanced use cases due to its ultra-low latency, ultra-high bandwidth, and high reliability.
Methodology
review
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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