US Transportation & Traffic Data Search

Search 21 US transportation data sources in one query — crash reports, traffic and transit data, infrastructure datasets, and registration or licensing records.

• ✅ Search 21 US transportation data sources across vehicle safety, traffic and transit, infrastructure, and registration datasets
• ✅ Get crash and collision records, MTA ridership, AADT counts, highway funding, road mileage, licensed-driver data, vehicle registrations, and EV registration records in one workflow
• ✅ Covers 4 vehicle-safety sources, 6 traffic and transit sources, 5 infrastructure sources, and 6 registration sources
• ✅ Export results as Excel, CSV, or JSON, or connect it to Apify MCP, API, Make, n8n, and Zapier
• ✅ Current Apify listing is pay per usage, so you can start with small runs and scale only when the workflow proves useful

Transportation data in the US is spread across city portals, transit agencies, DOT systems, DMV datasets, and federal infrastructure sources. Crash data sits in one place, ridership in another, registrations in another, and infrastructure funding elsewhere again. This Actor combines those public datasets into one search layer so you can run one query across the transportation records that matter for your workflow, then export or automate the results.

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What you can do with it

1. Search crash, collision, and inspection records

The vehicle-safety side of this Actor includes Chicago crashes, Chicago crash vehicles, NYC collisions, and New Jersey inspection data. That means you can search locations, streets, boroughs, corridors, vehicle terms, or inspection-related terms across several public safety datasets at once.

This is useful when you want one search layer for transportation safety signals rather than separate portal-by-portal lookups.

What you enter:

What	Example
Search term	Brooklyn, Atlantic Avenue, Chicago, or inspection
Categories	Vehicle safety only
How many results	50 per source

What you get back:

Source	Example fields
Chicago crashes and crash vehicles	Crash date, location, vehicle, crash or severity metadata
NYC collisions	Borough, street, injuries, fatalities, contributing factors
NJ inspections	Vehicle or inspection-related status and record metadata

This is useful for crash analysis, safety research, insurance context, fleet review, and AI assistants that need one transportation-safety search layer across multiple public datasets.

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2. Search traffic volumes, transit ridership, tolls, and ticket data

The traffic and transit side of this Actor includes NY AADT, MTA bridge and tunnel data, MTA subway ridership, E-ZPass data, and New York ticket-related datasets. That gives you a useful public-data slice for movement, ridership, and traffic-volume research.

This is not just one transit feed. It is a mixed traffic and transit discovery layer.

What you enter:

What	Example
Search term	Grand Central, Times Square, I-95, or George Washington Bridge
Categories	Traffic and transit only
How many results	50 per source

What you get back:

Source	Example fields
MTA subway and bridge/tunnel data	Station or crossing name, ridership or traffic volume, date
NY AADT / E-ZPass / ticket datasets	Corridor, usage, traffic, ticket, or conviction metadata

This is useful for urban research, site analysis, transit monitoring, traffic studies, and operational workflows that need one search layer across publicly available traffic and transit records.

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3. Search highway funding, fuel tax, mileage, and transit infrastructure data

The infrastructure side of this Actor includes fuel-tax records, highway funding, HPMS county data, road mileage, and transit urbanized-area statistics. That gives you a public-data entry point for transport infrastructure and finance context.

This is useful when your workflow is about network scale, funding, road condition context, or transit-system metrics rather than just crashes or ridership.

What you enter:

What	Example
Search term	New York, California, interstate, or county
Categories	Infrastructure only
How many results	50 per source

What you get back:

Source	Example fields
FHWA and HPMS datasets	Funding, fuel-tax, mileage, road-network, or county-level metadata
Transit UZA data	Urbanized-area transit statistics and reporting context

This is useful for infrastructure analysis, public-sector research, transportation consulting, network planning, and workflows that need road and transit context from public US datasets.

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4. Search registration, licensing, DMV, and EV adoption datasets

The registration side of this Actor includes licensed drivers, New York driver-license data, DMV facilities, vehicle registrations, Washington EV registrations, and New York highway mileage. That means you can search public registration and licensing records alongside the rest of the transportation stack.

This is especially useful when you care about fleet, driver, DMV, or EV-adoption context rather than only traffic incidents.

What you enter:

What	Example
Search term	Tesla, electric, Albany, or driver license
Categories	Registrations only
How many results	50 per source

What you get back:

Source	Example fields
Driver and vehicle registration datasets	Registration or license counts, make/model context, DMV-related metadata
EV and DMV facilities datasets	EV registration records, office locations, or related operational fields

This is useful for EV market monitoring, fleet research, DMV support workflows, transportation policy analysis, and AI assistants that need one search layer across public registration datasets.

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5. Use one Actor for mixed transportation discovery in AI and automation workflows

The main advantage of this Actor is that you can search transportation data across several public source families without integrating each city, state, and federal dataset separately.

Instead of wiring crash, transit, infrastructure, registration, and EV datasets into your workflow one by one, you can use one Actor as the discovery layer.

What you enter:

What	Example
Search term	Brooklyn
Categories	Vehicle safety + traffic and transit
How many results	25 per source

What your assistant or automation gets back:

Source family	Returned data
Vehicle safety	Crash, collision, and inspection records
Traffic and transit	Ridership, traffic volume, toll, and ticket records
Infrastructure	Funding, mileage, or network records if enabled
Registrations	Driver, vehicle, DMV, and EV records if enabled

This is useful for internal transportation assistants, route or location research, public-data automation, planning workflows, and spreadsheet-based analysis that needs one transportation-data entry point.

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How to use (no code required)

1. Click "Try for Free" at the top of this page
2. Type one or more search terms — locations, routes, stations, vehicle terms, bridges, corridors, or registration-related keywords
3. Choose which categories to search:
   • vehicle safety
   • traffic and transit
   • infrastructure
   • registrations
4. Set how many results you want per source
5. Click Start — the Actor queries the enabled transportation data sources and returns the results in the Dataset tab

You can then export the results as Excel, CSV, or JSON.

Because the Actor is listed as pay per usage, it is easy to begin with a small exploratory run, see which source families matter for your workflow, and then scale from there.

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What you get back

Each result comes back as one dataset row. The exact columns vary by source family, because a collision record, a subway ridership row, a highway-funding record, and an EV registration record do not share the same schema.

Across the dataset, you will typically see:

• name
• type
• status
• country
• authority
• _product_id
• _source
• _search_term
• _collected_at

Then source-specific fields such as:

• Vehicle safety: crash, collision, inspection, injury, fatality, or vehicle fields
• Traffic and transit: station, crossing, traffic volume, ridership, toll, or ticket fields
• Infrastructure: funding, mileage, HPMS, fuel-tax, or transit-statistics fields
• Registrations: driver, license, registration, DMV-facility, or EV-related fields

Every row tells you which source it came from and which search term matched, so it is easy to split outputs by source family and move them into downstream analysis or automation workflows.

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Coverage

This Actor currently searches 21 active US transportation data sources:

Category	Count	Coverage
Vehicle safety	4	Chicago crashes and crash vehicles, NYC collisions, NJ inspections
Traffic and transit	6	NY AADT, MTA bridge/tunnel, MTA subway, E-ZPass, and NY ticket datasets
Infrastructure	5	Fuel tax, highway funding, HPMS county data, road mileage, transit UZA
Registrations	6	Licensed drivers, NY driver and vehicle records, DMV facilities, WA EV registrations, NY highway mileage

The current active maps in the Actor are:

• 4 vehicle-safety sources
• 6 traffic and transit sources
• 5 infrastructure sources
• 6 registration sources

That matters because this Actor is not one unified transportation database. It is a combined public-data discovery layer across crash, transit, infrastructure, and registration source families.

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Pricing

This Actor is currently listed on Apify as pay per usage.

The safest place to confirm the live commercial terms is the pricing tab:

• https://apify.com/lentic_clockss/us-transportation-search/pricing

If you want to keep runs small, the easiest approach is to:

• search only the categories you actually need
• start with one or two search terms
• lower maxResultsPerSource for exploratory runs

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Connect to your tools

You can use this Actor directly in the Apify UI, or connect it to automation and AI workflows:

Platform	How to connect
Apify UI	Run it directly and export results
Apify API	Trigger runs and fetch datasets programmatically
Make.com	Use the Actor ID lentic_clockss/us-transportation-search
n8n / Zapier / ChatGPT / Claude	Use the same Actor ID via Apify MCP or API

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• US Education Data Search — education and school datasets
• US Financial Data Search — finance and institution datasets
• Canada Government Contracts Search — public procurement discovery

→ Browse all Actors: apify.com/lentic_clockss

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Also Available

• Direct API: https://opendata.best/api/v1/data
• Postman Collection: Fork and test
• GitHub: Collection source files