Automated and Connected Vehicle Implications and Analysis
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Summary
This report evaluates the current state and future implications of automated and connected vehicles (ACVs), with a specific focus on their integration with electric vehicles (EVs). Conducted by the Electric Vehicle Transportation Center at the University of Central Florida, the study aims to assess ACV technologies, existing laws, and policies to determine appropriate vehicle applications and the role of EVs in this emerging transportation landscape. The research is motivated by the potential for ACVs to fundamentally transform the U.S. transportation network by significantly reducing accidents, fuel consumption, pollution, and congestion costs. The methodology involves a comprehensive review of technological developments, regulatory frameworks, and case studies. The authors analyze SAE International’s six-level classification system for driving automation, ranging from Level 0 (no automation) to Level 5 (full autonomy). The report examines federal actions, including policies from the U.S. Department of Transportation (USDOT) and funding initiatives from the Department of Energy (DOE), such as the NEXTCAR program. It also reviews state-level legislative actions, noting that thirteen states and Washington D.C. had enacted autonomous vehicle legislation by early 2017. A specific case study of the Florida Department of Transportation’s Automated Vehicles initiative illustrates state-level implementation strategies. Key findings indicate that autonomous vehicle development, connected vehicle safety applications, and the interaction between autonomous and electric vehicles are the three areas of greatest activity. The report argues that electric propulsion will likely dominate future ACV fleets due to regulatory pressures regarding urban emissions and technical advantages. EVs offer fewer moving parts, reduced maintenance, and compatibility with "drive-by-wire" controls. Furthermore, wireless charging integrates seamlessly with autonomous systems, allowing vehicles to self-align and recharge efficiently. The study highlights that ACVs could reduce driving fatalities by up to 90% and save approximately $190 billion annually in U.S. healthcare costs. However, challenges remain, including liability determination, software reliability, public acceptance, and operational difficulties in extreme weather conditions. The significance of this work lies in its conclusion that ACV and EV technologies are converging and will inevitably merge. The authors assert that partnerships between ACV and EV stakeholders are essential to facilitate this integration. The report underscores the massive economic potential of the sector, citing multi-billion dollar investments from automakers and ride-sharing companies. By bridging the divide between automation and electrification, the transportation system can achieve greater efficiency, safety, and sustainability, moving toward the USDOT’s vision of eliminating roadway fatalities.
Key finding
Electric propulsion will likely dominate future automated and connected vehicles due to regulatory requirements for zero urban emissions and the technical advantages of electric systems for automated control functions.
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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- Theoretical Contribution: conceptual framework