The success of a national autonomous freight network hinges on addressing a key question: How will autonomous trucking affect safety and the workforce? Recent UC Davis research finds that these issues are deeply intertwined. Decisions about workforce roles shape safety outcomes, and safety policies, in turn, shape labor markets. This project examines both dimensions. On the safety side, prior research from this research team developed a set of human-centered safety metrics to evaluate shared safety responsibilities of heavy-duty automated driving systems (ADS), including indicators for control transitions, alerts, fallbacks, and human-ADS trust. The research team then tested the performance of these metrics in a driving simulator under low- and high-traffic conditions. On the workforce side, they investigated how non-driving tasks vary across freight systems and how staffing needs might evolve across freight applications as automation advances. More work is needed to convey the findings from these highly technical studies into practical tools that policymakers, regulators, and industry stakeholders can use to guide real-world implementation. This project turns those findings into action. The research team will synthesize and operationalize key insights from this research into an Autonomous Trucking Workforce & Safety Guidebook and Resource Hub, informed by a series of stakeholder workshops. This project will produce a set of practical tools to support a safer transportation system and an emerging innovation workforce.