What is traffic intensity on Map AI?

Traffic intensity on Map AI is the number of vehicles per day on an average mile of a given road class in an area, computed as the length-weighted average of the AADT of every road segment of that class inside the area. In Miami-Dade County an average motorway mile carries 61,049 vehicles a day, an average residential mile 368.

How is traffic intensity different from AADT?

AADT, annual average daily traffic, is the daily vehicle count for one road segment. Traffic intensity averages the AADT of all roads of one class inside an area, weighting each segment by its length, so a county or a 3-mile radius gets a comparable figure even though it contains thousands of roads with very different volumes.

How does Map AI calculate vehicle miles travelled (VMT) for an area?

Map AI calculates VMT by multiplying the AADT of every road segment by its length in miles inside the area and summing the results, which equals traffic intensity times road length summed over road classes. Miami-Dade County's roads carry about 48.9 million vehicle miles a day, or 17.9 miles per resident.

Where does Map AI's traffic data come from?

Map AI's road traffic volumes come from TrafficZoom, the traffic platform of Ticon. TrafficZoom calibrates GPS and connected-vehicle samples against state DOT and FHWA detector counts and estimates AADT for about 16 million US road segments; Map AI maps those roads onto counties, states, hexagons and custom areas.

What share of US driving happens on motorways?

Motorways carry 46% of the vehicle miles travelled that Map AI counts on US roads while making up only 1.9% of road miles. Residential streets are the opposite: 43% of road miles and less than 5% of driving, which is why Map AI reports traffic separately for each road class.

What is destination traffic in a Map AI sales forecast?

Destination traffic is the number of vehicles per day that enter a trade area and stay, rather than pass through. TrafficZoom counts traffic on every road crossing the trade area's boundary, hour by hour in both directions, and sums the hours in which more vehicles arrive than leave.

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How Map AI Measures Traffic: AADT, Traffic Intensity and VMT Explained

November 9, 2026

8 min to read

By Tim Oshchepkov, CTO at Map AI. Updated November 9, 2026.

Motorways make up 1.9% of US road miles yet carry 46% of all the driving Map AI counts. Residential streets are 43% of the road network and carry less than 5%.

That gap is why one "traffic" number for an area can mislead, and why Map AI reports traffic by road class. Below: what traffic data Map AI has, where it comes from, and the exact formulas behind every traffic figure on the map.

What traffic data Map AI has

Traffic volume on every road: annual average daily traffic (AADT) for about 16 million US road segments, from local streets to interstates.
The road network: every public road from OpenStreetMap, measured to the meter and sorted into 13 road classes, from motorway to service road.
Destination traffic: a live estimate of how many vehicles a day come to a trade area and stay, used in the Map AI sales forecast.

From these Map AI derives traffic intensity (vehicles per day on an average mile of road) and cumulative traffic intensity (vehicle miles travelled per day).

Where the road volumes come from

The per-road volumes come from TrafficZoom, the traffic platform of Ticon, the company Map AI grew out of. Map AI takes TrafficZoom's estimates as they are and does the geography: it places every road into every area you can select and aggregates the numbers. TrafficZoom builds each estimate in four steps:

Ground truth: counts from permanent and portable detectors published by state departments of transportation and the Federal Highway Administration.
Sample: GPS and connected-vehicle traces matched to the road network give a sample count on every segment, including roads with no detector.
Calibration: at each detector, the share of real traffic the sample captures is measured; detectors that disagree sharply with similar neighbours are dropped.
Expansion: for every other segment, that share is interpolated from nearby detectors, weighted by network distance and road similarity. Sample count divided by share gives the segment's volume.

What AADT means

AADT is the number of vehicles passing one point of a road in a year, both directions, divided by 365. A road with an AADT of 20,000 sees 20,000 vehicles on an average day. AADT belongs to one road segment: a county or a 3-mile radius has no AADT of its own, because it holds thousands of roads with very different volumes. That is why Map AI turns segment AADT into two area measures.

Traffic intensity: the exact formula

Traffic intensity (TI) answers one question: on an average mile of this kind of road in this area, how many vehicles pass per day? It is computed separately for each road class, because a motorway and a residential street are not comparable.

TI (c, A) = \frac{\sum_{i} {AADT}_{i} \times L_{i}}{\sum_{i} L_{i}}

TI(c, A): traffic intensity: vehicles per day on an average mile of class-c road in area A
A: the area: a county, a state, a radius or a drawn polygon
c: a road class, such as motorway, primary or residential
i: each road segment of class c inside A
AADT_i: annual average daily traffic on segment i, vehicles per day
L_i: length of segment i inside A; roads crossing the boundary are clipped

This is a length-weighted average: a two-mile stretch counts twice as much as a one-mile stretch, so the result means "an average mile", not "an average segment".

From hexagons to counties and states

Map AI computes TI first on a grid of hexagons of about 2 square miles each (H3 resolution 7) covering the whole country, then builds larger areas from the hexagons with the same weighting:

TI (c, county) = \frac{\sum_{h} TI (c, h) \times L (c, h)}{\sum_{h} L (c, h)}

h: each hexagon in the county
L(c, h): total length of class-c road in hexagon h

Weighting each hexagon by its own road length makes this equal to a length-weighted average over all the road segments in those hexagons. Places, states and the country are built the same way. For a radius, a drive-time area or a drawn polygon, Map AI clips the roads to that shape and applies the first formula directly.

Worked example: Miami-Dade County, Florida

Road class	Road miles	TI, vehicles per day
Motorway	307	61,049
Trunk	217	19,676
Primary	455	19,497
Secondary	655	11,195
Tertiary	1,287	3,709
Unclassified	223	753
Residential	5,690	368
Service	4,560	85

Ramps (the _link classes) are left out of the table for space but included in every calculation.

An average motorway mile in Miami-Dade carries 166 times the traffic of an average residential mile. Any single number for the county has to decide how to combine these rows.

Combining road classes: highways and local streets

For one figure across several classes, Map AI applies the same length weighting once more:

TI (g, A) = \frac{\sum_{c \in g} TI (c, A) \times L (c, A)}{\sum_{c \in g} L (c, A)}

g: a group of road classes (below)
L(c, A): total length of class-c road in area A

Highways: motorways and trunk roads with their ramps.
Other streets: primary, secondary, tertiary, residential and unclassified roads with their ramps.
All public roads: both groups. Service roads, which in OpenStreetMap are mostly driveways, alleys and parking aisles, are left out.

Miami-Dade gets 34,197 vehicles a day on an average highway mile, 2,790 on other streets, and 5,337 across all public roads. Local streets dominate the length, so they pull the all-roads figure down, which is a fair picture of an average mile of road there.

Cumulative traffic intensity: vehicle miles travelled

Traffic intensity describes a typical road. Cumulative traffic intensity describes the whole area: the total distance driven on its roads in a day, in vehicle miles travelled (VMT). One car driving one mile is one vehicle mile.

VMT (A) = \sum_{c} TI (c, A) \times L (c, A) = \sum_{i} {AADT}_{i} \times L_{i}

VMT(A): vehicle miles travelled per day on all roads in area A
c, i: every road class, and every road segment, in A
L: road length, here in miles

A half-mile segment with an AADT of 10,000 adds 5,000 vehicle miles a day. Miami-Dade's roads carry about 48.9 million vehicle miles a day, 17.9 per resident. Its 307 miles of motorway, 2.2% of the road length, carry 38% of that driving; residential streets, 42% of the length, carry 4%.

The national picture

Road class	Share of US road miles	TI, vehicles per day
Motorway	1.9%	23,406
Trunk	1.7%	6,159
Primary	3.2%	4,518
Secondary	5.1%	2,455
Tertiary	8.6%	765
Residential	43.5%	105
Unclassified	9.5%	66
Service	25.8%	25

An average motorway mile in Miami-Dade carries 2.6 times the national motorway average, and an average residential mile 3.5 times the national residential average. Dense metros load more traffic onto every class of road, not only their freeways, so per-class traffic intensity shows how busy a place is better than road length or population alone.

Destination traffic: who comes to stay

For a business, passing cars are only part of the story. The Map AI sales forecast also asks TrafficZoom how many vehicles a day enter a trade area and stay, rather than drive through. TrafficZoom takes every road crossing the trade area's boundary, splits it into inbound and outbound directions, and spreads each road's AADT over the 24 hours of the day:

D = \sum_{t : net (t) > 0} net (t), net (t) = in (t) - out (t)

D: destination traffic, vehicles per day
t: hour of the day, 0 to 23
in(t), out(t): vehicles crossing the boundary into and out of the trade area in hour t

Through traffic enters and leaves within about the same hour and largely cancels out. In the hours when more vehicles arrive than leave, the area is filling with people who came to be there; summing those hours estimates daily visits by car. Summing the whole day would come out near zero for any area that empties again by night.

AADT, traffic intensity or VMT: which to use

Measure	What it tells you	Use it for
AADT	Vehicles a day on one road segment	A specific site: how many cars pass the storefront
Traffic intensity	Vehicles a day on an average mile of one road class in an area	Comparing how busy roads are across areas of any size
VMT	Total miles driven in an area per day; grows with area size	Comparing total driving activity of equal-size areas

Traffic intensity is an average, so 2,790 vehicles a day on Miami-Dade's local streets does not mean any one street carries 2,790. For a site decision, check the AADT of the road itself in TrafficZoom. As a rule of thumb from Ticon's practical guide to reading traffic count data for retail site selection, an AADT above 10,000 is generally considered acceptable for retail, and above 4,000 can work in some cases. All of these volumes are modelled estimates calibrated against detector counts, tighter near a detector than far from one.

Other traffic-related data on Map AI

From the US Census Bureau's American Community Survey, Map AI also maps car ownership and how residents get to work:

Households by number of vehicles: none, one, two, three, four or more.
Commute time: median one-way travel time to work, and its distribution.
Commute mode: car, public transit, walking, bicycle, motorcycle, taxi or working from home.
Departure time to work: when residents leave home, which shapes the morning peak.

Road density (miles of road per square mile) comes from the same OpenStreetMap network used above.

See traffic for any US area. Pick a county or draw a radius and check traffic intensity by road class next to population and income.

Open the traffic map

For how total US driving has moved against commuting since 2009, see US traffic volume vs commute time.

Sources: road segment traffic volumes from TrafficZoom by Ticon; road network from OpenStreetMap; vehicles and commuting from the US Census Bureau American Community Survey; retail AADT thresholds from Ticon's guide to reading traffic count data; aggregation, traffic intensity and VMT by Map AI.

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