Traffic Technicians
In short: today's best AI models could do about 62% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 80% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 20% of the time, stays with people.
Conduct field studies to determine traffic volume, speed, effectiveness of signals, adequacy of lighting, and other factors influencing traffic conditions, under direction of traffic engineer.
7,860 people do this job in the US. $59,090 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on25 h
- A person checks AI's work0 h
- Desk work AI can't do yet7 h
- Stays with people8 h
Traffic Technicians, now: of a 40-hour week, AI could take on 25 hours, 0 hours become checking its work, 7 hours are desk work it can't do yet, and 8 hours stay with people.
The largest pieces: Prepare drawings of proposed signal installations or other control devices, using drafting instruments or computer-automated drafting equipment (about 9 h); Study factors affecting traffic conditions, such as lighting or sign and marking visibility, to assess their effectiveness (about 5 h); Plan, design, and improve components of traffic control systems to accommodate current or projected traffic and to increase usability and efficiency (about 4 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 80%
- 0%
- 20%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 15%. Today's estimate: 62%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.011% went to this job's tasks in May 2026, the 412th largest of the 447 jobs that showed up at all; 1 of its 22 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0077% to 0.011% (released February and March 2025); 0.0078% to 0.01% (August 2025 to February 2026); 0.011% to 0.011% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0077% | 560 of 708 | 2 of 22 |
| Released March 2025 | 0.011% | 499 of 703 | 4 of 22 |
| The week of Aug 4, 2025 (released September 2025) | 0.0078% | 488 of 655 | 1 of 22 |
| The week of Nov 13, 2025 (released January 2026) | 0.0087% | 501 of 672 | 1 of 22 |
| The week of Feb 5, 2026 (released March 2026) | 0.01% | 492 of 677 | 1 of 22 |
| April 2026 (released June 2026) | 0.011% | 396 of 434 | 1 of 22 |
| May 2026 (released June 2026) | 0.011% | 412 of 447 | 1 of 22 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 31% of this job's working time as physical work. For 20% of the working time, a robot has been shown doing most of the task somewhere: 11% in a purpose-built cell, 4% in a structured facility, 5% in any setting. 0.35 of 3, the 368th highest of the 923 jobs.
- Not physical 69%
- No robot shown 11%
- In a purpose-built cell 11%
- In a structured facility 4%
- In any setting 5%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 22 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Prepare drawings of proposed signal installations or other control devices, using drafting instruments or computer-automated drafting equipment.Done more than monthly by most who do it. | 29% | 5 h1.7 h to 1.7 work days | 80%Half by now | |
| Plan, design, and improve components of traffic control systems to accommodate current or projected traffic and to increase usability and efficiency.Done more than monthly by most who do it. | 20% | 1 work day3.3 h to 4.2 work days | 52%Half by now | |
| Study factors affecting traffic conditions, such as lighting or sign and marking visibility, to assess their effectiveness.Done more than monthly by most who do it. Robots: in a purpose-built cell, RoadVista Model 933 Retroreflectivity Goniometer System (sold). Anthropic's rating. | 12% | 2.5 h50 min to 6.7 h | 96%Half by now | |
| Analyze data related to traffic flow, accident rates, or proposed development to determine the most efficient methods to expedite traffic flow.Done more than monthly by most who do it. | 8% | 5 h1.7 h to 2.1 work days | 73%Half by now | |
| Provide technical supervision regarding traffic control devices to other traffic technicians or laborers.Done more than monthly by most who do it. | 8% | 1.3 h25 min to 3.3 h | Stays with people | |
| Gather and compile data from hand count sheets, machine count tapes, or radar speed checks and code data for computer input.Done more than monthly by most who do it. | 3% | 1.3 h25 min to 2.5 h | 100%Half by now | |
| Study traffic delays by noting times of delays, the numbers of vehicles affected, and vehicle speed through the delay area.Done more than yearly by most who do it. Robots: in any setting, Elistair Safe-T tethered drone station + DataFromSky FLOW analytics (sold). Anthropic's rating. | 2% | 2.5 h50 min to 5 h | Stays with people | |
| Visit development or work sites to determine projects' effect on traffic and the adequacy of traffic control and safety plans or to suggest traffic control measures.Done more than yearly by most who do it. Robots: no robot shown. Anthropic's rating. | 2% | 2.1 h50 min to 4.2 h | Stays with people | |
| Interact with the public to answer traffic-related questions, respond to complaints or requests, or discuss traffic control ordinances, plans, policies, or procedures.Done more than yearly by most who do it. | 2% | 25 min8 min to 1.3 h | 100%Half by now | |
| Establish procedures for street closures or for repair or construction projects.Done more than yearly by most who do it. | 2% | 2.5 h1.3 h to 6.7 h | 99%Half by now | |
| Lay out pavement markings for striping crews.Done more than monthly by most who do it.Robots: in any setting, TinyMobileRobots TinySurveyor Terra (deployed). Anthropic's rating. | 2% | 2.1 h50 min to 5 h | Stays with people | |
| Operate counters and record data to assess the volume, type, and movement of vehicular or pedestrian traffic at specified times.Done more than yearly by most who do it. | 2% | 1.7 h50 min to 5 h | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Civil Engineering Technologists and Technicians62% now, 82% by 2028
- Construction and Building Inspectors49% now, 51% by 2028
- Air Traffic Controllers73% now, 73% by 2028
- Railroad Conductors and Yardmasters33% now, 33% by 2028
- Highway Maintenance Workers0% now, 0% by 2028
- Transportation Vehicle, Equipment and Systems Inspectors, Except Aviation25% now, 29% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Traffic Technicians is within reach of AI now?
- An estimated 62% of the working time is within reach of AI models now and 80% by the end of 2028, on METR's long-run pace at four in five (79% to 80% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Traffic Technicians come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Prepare drawings of proposed signal installations or other control devices, using drafting instruments or computer-automated drafting equipment (80% of the task's time now, 100% by the end of 2028); Study factors affecting traffic conditions, such as lighting or sign and marking visibility, to assess their effectiveness (96% of the task's time now); and Plan, design, and improve components of traffic control systems to accommodate current or projected traffic and to increase usability and efficiency (52% of the task's time now, 100% by the end of 2028).
- Which tasks of Traffic Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Provide technical supervision regarding traffic control devices to other traffic technicians or laborers; Study traffic delays by noting times of delays, the numbers of vehicles affected, and vehicle speed through the delay area; and Visit development or work sites to determine projects' effect on traffic and the adequacy of traffic control and safety plans or to suggest traffic control measures. Together such tasks are about 20% of the working time.
- Do people already use AI for the work of Traffic Technicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 412th largest share of the 447 jobs that showed up; 1 of its 22 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Traffic Technicians?
- Anthropic's robot exposure rating (September 2026) finds 31% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 20% of the working time, 5% in any setting. Its index is 0.35 of 3. One example: Elistair Safe-T tethered drone station + DataFromSky FLOW analytics for "study traffic delays by noting times of delays, the numbers of vehicles affected, and vehicle speed through the delay area". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 22 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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