New Brunswick Innovation Hub Smart Mobility Testing Ground
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Summary
This report details the construction, deployment, and operational framework of the New Brunswick Innovation Hub Smart Mobility Testing Ground (SMTG), now designated as DataCity SMTG. Led by Rutgers University’s Center for Advanced Infrastructure and Transportation in collaboration with industry partners, the project establishes a living laboratory in downtown New Brunswick, New Jersey, to support the research, development, and testing of Connected and Automated Vehicle (CAV) technologies. The initiative aligns with the New Jersey Department of Transportation’s “Commitment to Communities” and the Federal Highway Administration’s goals for accelerated V2X deployment, aiming to provide equitable smart mobility services that do not require expensive on-board vehicle units. The project instrumented a 2.1-mile multi-modal corridor along Route 27 and Route 18 with 12 roadside locations featuring self-driving-grade sensing infrastructure. This includes autonomous-grade LiDAR sensors, high-definition cameras, and differential GPS base stations. The system architecture utilizes edge processors (Nvidia Jetson AGX Xavier) and fog processor nodes (Nvidia Jetson AGX Orin) to handle low-latency data processing locally, reducing bandwidth demands on the central network. Data is transmitted via fiber and cellular connectivity to a Smart Mobility Management Center, which serves as the operational hub for data analytics, application hosting, and traffic monitoring. The team also developed a digital twin platform using CARLA and SUMO simulators, creating a 3D virtual replica of the corridor based on mobile LiDAR scanning and infrastructure modeling to facilitate early-stage R&D and trajectory reconstruction. DataCity SMTG provides four primary services: a technology proving ground for transportation agencies, a high-resolution smart mobility data hub, a digital twin platform for simulation, and open-road testing facilities. The report documents the validation of C-V2X applications, including the use of the BlueCity platform to detect traffic conflicts and calculate surrogate safety measures such as Post Encroachment Time (PET). The study also analyzed LiDAR blind zones caused by vehicle occlusions, evaluating sensor configurations to optimize coverage. Additionally, the report reviews the legislative landscape for automated vehicles in New Jersey and the United States, identifying regulatory frameworks relevant to testing automated transit systems. The significance of this work lies in the creation of a scalable, community-focused testing environment that bridges the gap between controlled simulation and real-world deployment. By providing high-resolution data and a digital twin, DataCity supports the certification and evaluation of smart mobility technologies for diverse stakeholders, including academic institutions, OEMs, and government agencies. The project also outlines a business plan for sustainable long-term operations, including revenue models and governance structures, ensuring the testing ground can continue to serve as a catalyst for economic development and transportation innovation in the region.
Key finding
The DataCity Smart Mobility Testing Ground successfully deployed a comprehensive roadside sensor and computing infrastructure that enables high-resolution data collection and smart mobility application testing for all travelers without requiring specialized onboard vehicle equipment.
Methodology
field_study
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 | — | — | 24 | 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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- Methodological Resource: tool software, dataset resource, validation psychometrics