Driving Automation Systems in Long-Haul Trucking and Bus Transit: Preliminary Analysis of Potential Workforce Impacts - Report to Congress, January 2021
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Summary
This report, commissioned by the 2018 Consolidated Appropriations Act, analyzes the potential workforce impacts of Advanced Driver Assistance Systems (ADAS) and Highly Automated Vehicles (HAV) on professional drivers in long-haul trucking and transit bus sectors. Developed by the U.S. Department of Transportation in coordination with the Departments of Labor, Commerce, and Health and Human Services, the study addresses congressional concerns regarding labor displacement, safety risks, and training needs associated with driving automation. The research aims to provide a comprehensive assessment of how these technologies may alter job responsibilities, wages, and employment stability for commercial driver’s license holders. The methodology relies primarily on a review of published literature, analysis of existing datasets, and stakeholder consultation, rather than primary data collection or predictive modeling. The authors conducted a Request for Comments, receiving 31 responses from industry groups, labor unions, and safety advocates, and held a stakeholder workshop featuring diverse perspectives. The report utilizes SAE International J3016 terminology to define automation levels, distinguishing between ADAS (Levels 0–2) and Automated Driving Systems (ADS) (Levels 3–5). Due to significant uncertainties regarding the timeline for commercial adoption and the specific operational design domains of future technologies, the report avoids definitive predictions, focusing instead on synthesizing existing evidence and identifying potential scenarios. The findings indicate that the adoption of driving automation will likely be gradual and uncertain. Current Level 1 and 2 ADAS technologies are not expected to cause driver displacement and may improve safety and operations. However, the eventual adoption of Level 4 or 5 ADS could supplant certain driving tasks, potentially leading to transitional unemployment for some workers. The report identifies several mitigating factors: the long time horizon for widespread adoption allows for natural workforce attrition, particularly given the older age profile of many current drivers; automation is expected to lower freight costs and enhance productivity, creating new jobs in transportation, logistics, and emerging sectors; and existing Department of Labor programs offer retraining resources. The study also notes that while long-haul trucking may be affected sooner due to simpler highway operating environments, transit bus automation remains in early pilot stages. The significance of this report lies in its conclusion that while driving automation poses risks of job displacement, the impacts will likely be absorbed over decades through natural turnover, job creation, and retraining. The authors emphasize that the specific trajectory of employment changes is highly uncertain and dependent on technological maturity, regulatory frameworks, and business model evolution. The report underscores the importance of federal roles in ensuring safe integration of automated vehicles and supporting workforce adaptation, recommending continued monitoring and future reexaminations as technologies mature. It serves as a foundational analysis for policymakers to understand the complex interplay between technological innovation and labor market dynamics in the transportation sector.
Key finding
Widespread adoption of Level 4 or 5 driving automation is not imminent, and natural workforce attrition is expected to mitigate significant driver displacement in the long-haul trucking and transit bus sectors.
Methodology
review
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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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