Truck Platooning Early Deployment Assessment– Independent Evaluation: Performance Measures for Evaluating Truck Platooning Field Deployments
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Summary
This report, produced by Noblis Inc. for the U.S. Department of Transportation’s Intelligent Transportation Systems Joint Program Office, addresses the need for standardized performance measures to evaluate truck platooning field deployments. Truck platooning, a cooperative automated driving system using vehicle-to-vehicle (V2V) communications, allows trucks to follow each other closely to improve fuel efficiency and safety. The study was motivated by the Federal Highway Administration’s “Truck Platooning Early Deployment Assessment” project, which aims to assess the operational, safety, and economic impacts of this technology before widespread commercial adoption. Specifically, the report supports Phase 1 of this assessment, where three teams (Battelle, California PATH, and CDM Smith) developed concepts for Phase 2 field tests. The primary objective was to define requirements and synthesize a comprehensive list of performance measures to guide the evaluation of these future field deployments. The research methodology employed a two-step synthesis approach. First, the authors reviewed Test and Evaluation Plan reports submitted by the three Phase 1 awardees to identify performance measures proposed for their specific Phase 2 deployments. Second, they conducted a literature review of other past and ongoing truck platooning projects, including the commercial demonstration in Texas and the European Union’s ENSEMBLE project, to identify additional measures. These findings were synthesized to create a robust framework for evaluation. The performance measures were categorized into eight key areas of interest identified by the FHWA: Platoon Operational Characteristics, Safety, Mobility, Energy and Emissions, Fleet Operator and Driver Impacts, Infrastructure Impacts, State and Local Government Impacts, and Vehicle Equipment Design Implications. For each measure, the report details its definition, interpretation, data needs, evaluation approach, and associated challenges. The report identifies specific performance measures for each category. For Platoon Operational Characteristics, measures include platoon formation time and the number of lane changes during formation, which assess efficiency and driver behavior. Safety measures focus on driver and vehicle performance and interactions with surrounding traffic. Mobility measures evaluate impacts on congestion and traffic flow under various roadway conditions. Energy and Emissions measures quantify fuel savings and pollutant reductions. Fleet Operator and Driver Impacts include metrics on driver fatigue, workload, and operational costs. Infrastructure, Government, and Vehicle Equipment measures address requirements for roadway support, policy enforcement, and necessary vehicle modifications. The report emphasizes that these measures must be used within the appropriate context, noting that they are not intended to evaluate the maturity level of specific technologies but rather the impacts of the platooning operations themselves. The significance of this work lies in providing transportation agencies and researchers with a standardized framework for evaluating truck platooning. By synthesizing measures from multiple sources, the report ensures that future field tests can capture a holistic view of the technology’s impacts, from fuel savings to safety risks and infrastructure needs. The authors conclude that while the report presents a comprehensive list of potential measures, the actual metrics used in Phase 2 will depend on the specific evaluation plans of the awardees and the quality of field data collected. This guidance is critical for isolating and quantifying the true impacts of truck platooning on the transportation system, thereby informing policy and operational decisions for the commercial trucking industry.
Key finding
The study establishes a comprehensive set of performance measures across eight categories to evaluate truck platooning field deployments, including platoon formation time, lane change rates, and speed variability.
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 | — | — | 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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- Applied Guidance: countermeasure evaluation
- Methodological Resource: validation psychometrics, tool software