Prepare studies for proposed transportation projects. Gather, compile, and analyze data. Study the use and operation of transportation systems. Develop transportation models or simulations.
U.S. Workers
36,970
Median Salary
$100,340
10-Year Growth
-1.7%
Annual Openings
3,200
Typical entry: Bachelor's degree
21 of 22 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Design transportation surveys to identify areas of public concern.
AI: Fully automatable - AI can design effective transportation surveys, including question wording, sampling strategies, and analysis plans, following best practices and constraints.
Interpret data from traffic modeling software, geographic information systems, or associated databases.
AI: Fully automatable - AI can interpret outputs from traffic models and GIS, extract patterns, run analyses, and produce explanations and visualizations at a level useful for planners.
Prepare reports or recommendations on transportation planning.
AI: Fully automatable - AI can synthesize analyses, create structured reports, and produce actionable recommendations for transportation planning, subject to human review for local and political nuances.
Analyze information related to transportation, such as land use policies, environmental impact of projects, or long-range planning needs.
AI: Fully automatable - AI can reliably analyze policy documents, environmental datasets, and run long-range scenario analyses given appropriate data, automating most analytical work.
Prepare necessary documents to obtain planned project approvals or permits.
AI: Fully automatable - AI can assemble, populate, and draft permit and approval documents from templates and data, automating the majority of document preparation tasks.
Analyze information from traffic counting programs.
AI: Fully automatable - AI can fully process traffic counting datasets, perform cleaning, classification, trend analysis, and produce reports and visualizations automatically.
Recommend transportation system improvements or projects, based on economic, population, land-use, or traffic projections.
AI: Partial - AI can synthesize economic, demographic, land-use, and traffic projections to recommend improvements, but often cannot fully assess local feasibility, political constraints, or engineering details without human input.
Define regional or local transportation planning problems or priorities.
AI: Partial - AI can identify and prioritize planning issues from data and documented objectives, but defining priorities requires stakeholder engagement and local judgment that AI alone does not provide.
Participate in public meetings or hearings to explain planning proposals, to gather feedback from those affected by projects, or to achieve consensus on project designs.
AI: Partial - AI can prepare presentations, summarize feedback, and assist facilitation, but cannot fully replicate real-time human negotiation, trust-building, and legal standing in public meetings or hearings.
Design new or improved transport infrastructure, such as junction improvements, pedestrian projects, bus facilities, or car parking areas.
AI: Partial - AI can generate conceptual designs and run simulations but cannot fully replace site-specific engineering judgment, field surveys, stakeholder coordination, and regulatory signoffs.
Collaborate with engineers to research, analyze, or resolve complex transportation design issues.
AI: Partial - AI can assist engineers by analyzing data, proposing solution options, and documenting findings, but cannot fully substitute human collaboration and domain expertise for resolving complex design issues.
Evaluate transportation project needs or costs.
AI: Partial - AI can produce needs assessments and cost estimates from models and historical data but typically requires human validation for local pricing, procurement practices, and contingency/risk judgment.
Collaborate with other professionals to develop sustainable transportation strategies at the local, regional, or national level.
AI: Partial - AI can model sustainability scenarios and draft strategy options, but effective multi-stakeholder coordination, policy negotiation, and political judgment remain human-led.
Develop computer models to address transportation planning issues.
AI: Partial - AI can generate prototype code and models and accelerate development, but building complex, validated transportation models requires expert calibration, validation, and judgment.
Develop or test new methods or models of transportation analysis.
AI: Partial - AI can assist in creating and testing new analytical methods by running experiments and proposing approaches, but leading research, conceptual breakthroughs, and rigorous validation still need human researchers.
Prepare or review engineering studies or specifications.
AI: Partial - AI can draft and perform preliminary reviews of engineering studies and specifications for consistency and standards, but final technical approval and safety-critical review require licensed engineers.
Review development plans for transportation system effects, infrastructure requirements, or compliance with applicable transportation regulations.
AI: Partial - AI can analyze plans, model impacts, and flag likely compliance issues but cannot fully replace expert judgment, local knowledge, or legal authority.
Evaluate transportation-related consequences of federal or state legislative proposals.
AI: Partial - AI can model and quantify likely transportation effects of legislation and draft analyses, but evaluating political tradeoffs and legal/policy judgment requires humans.
Produce environmental documents, such as environmental assessments or environmental impact statements.
AI: Partial - AI can draft structured environmental assessments and analyze data, but cannot conduct site-specific fieldwork, public consultation, or assume legal responsibility for final documents.
Direct urban traffic counting programs.
AI: Partial - AI and automated sensor systems can run and process traffic counts and schedule operations, but program direction, field troubleshooting, and stakeholder coordination require human oversight.
Define or update information such as urban boundaries or classification of roadways.
AI: Partial - AI can analyze GIS data, remote sensing, and traffic patterns to propose boundary or roadway classification updates, but final policy decisions and local context validation need humans.
Represent jurisdictions in the legislative or administrative approval of land development projects.
AI: Not automatable - Representing jurisdictions in approvals requires legal standing, negotiation, and political judgment that AI cannot perform.