Aligning Traffic Management Center Staffing Capabilities for the Future of Systems Operations

Burgess, Lisa; Dale, Jeffery W. · 2024 · ROSA P / United States. Federal Highway Administration. Office of Safety and Operations Research and Development

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Summary

This report, published by the Federal Highway Administration in 2024, addresses the critical challenge of aligning Traffic Management Center (TMC) staffing capabilities with the evolving demands of next-generation Traffic Management Systems (TMSs). As transportation agencies transition from legacy systems to more complex, automated, and data-driven operations, the technical skills and operational roles required of TMC staff are shifting significantly. The study was motivated by widespread workforce challenges, including accelerated retirements, a loss of institutional knowledge, and difficulties in recruiting staff with specialized technical expertise such as data analysis, software integration, and advanced computing. The report aims to provide agencies with strategies to assess current staffing needs, define required knowledge, skills, and abilities (KSAs), and implement effective staffing plans that support proactive system management rather than passive monitoring. The research methodology involved a comprehensive review of national resources and interviews with State Departments of Transportation (DOTs) to identify best practices and common challenges. The report analyzes three primary staffing models: public sector staff, contractor staffing, and hybrid approaches. It examines how emerging technologies, such as artificial intelligence and decision-support tools, and new operating strategies like integrated corridor management and active traffic management, influence staff roles. The study provides detailed guidance on developing TMS staffing plans, including methods for deriving KSAs, updating job descriptions, and establishing training protocols. It also explores recruitment and retention strategies, highlighting the competitive nature of the technology labor market and the limitations of traditional public-sector compensation structures in attracting technical talent. Key findings indicate that agencies face significant hurdles in quantifying the specific technical skills needed for modern TMS operations and aligning these requirements with existing job classifications. The report identifies that while automation can streamline certain functions, it simultaneously increases the need for staff capable of managing complex analytics, calibrating AI systems, and making engineering judgments. The analysis of staffing approaches reveals distinct trade-offs: public sector staff offer stability but struggle with recruitment and career path flexibility for technical roles; contractor staffing provides scalability and specialized skills but may face retention issues due to contractual compensation limits; hybrid models attempt to balance oversight with operational flexibility. The report emphasizes that successful staffing requires clear documentation of processes, robust training beyond standard operating procedures, and leadership support for a culture of performance-based operations. The significance of this work lies in its practical guidance for transportation agencies seeking to maintain operational resiliency amidst workforce transitions and technological advancements. By providing sample job descriptions, staffing plan outlines, and comparative analyses of staffing models, the report enables agencies to proactively address staffing gaps. It underscores the importance of integrating staffing considerations into the early stages of TMS planning and development. Ultimately, the findings suggest that aligning staffing capabilities with future systems operations is essential for realizing the full benefits of advanced traffic management technologies, ensuring that agencies can effectively manage congestion, improve safety, and support multimodal coordination in an increasingly complex transportation environment.

Key finding

Agencies must align TMC staffing plans with evolving TMS capabilities by addressing challenges in recruiting, retaining, and training staff with the specific technical skills and knowledge required for next-generation, automated traffic management operations.

Methodology

field_study

Provenance

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