US Transportation & Traffic Data Search

Apify Actor that queries the SIP Public Data Gateway over HTTPS — no browser, no scraping. Provide search terms (location names, route identifiers, or keywords); the Actor queries up to 21 US transportation data products in parallel and returns normalized rows enriched with source metadata.

Features

• One search, 21 sources — Query crash reports, transit ridership, highway data, and vehicle registrations across Chicago, NYC, NJ, NY, and WA with a single keyword
• Official government data — All 21 products are sourced from public US federal and city/state transportation databases
• Structured JSON output — Every record includes _product_id, _source, _search_term, and _collected_at metadata for traceability
• Category toggles — Enable or disable four source categories (vehicle safety, traffic data, infrastructure, registrations) per run
• No upstream API keys needed — SIP handles authentication with all upstream transportation APIs
• Pure HTTP client — No browser overhead; uses httpx for fast, parallel requests

Example Output

[
  {
    "crash_date": "2024-06-12",
    "borough": "BROOKLYN",
    "on_street_name": "ATLANTIC AVENUE",
    "number_of_persons_injured": 2,
    "number_of_persons_killed": 0,
    "contributing_factor_vehicle_1": "Failure to Yield Right-of-Way",
    "vehicle_type_code1": "Taxi",
    "latitude": "40.6863",
    "longitude": "-73.9778",
    "_product_id": "us_transport_nyc_collisions",
    "_source": "nyc_collisions",
    "_search_term": "Brooklyn",
    "_collected_at": "2026-04-13T10:00:00Z"
  },
  {
    "station": "GRAND CENTRAL-42 ST",
    "line": "4 5 6",
    "ridership": 38754,
    "service_date": "2024-03-11",
    "_product_id": "us_transport_ny_mta_subway",
    "_source": "ny_mta_subway",
    "_search_term": "Grand Central",
    "_collected_at": "2026-04-13T10:00:00Z"
  }
]

What it does

• Searches across 21 active US transportation data products grouped into four toggleable categories: vehicle safety, traffic & transit, infrastructure, and registrations.
• All enabled product queries for a given search term execute concurrently via asyncio.gather, minimizing total run time.
• Each result row is enriched with _product_id, _source, _search_term, and _collected_at so you can trace every record back to its origin.
• Pure HTTP client (httpx) — no Playwright, no browser overhead.

Data sources

Category	SIP Product ID	Agency / Source
Vehicle Safety	us_transport_chicago_crashes	Chicago DOT — crash reports
	us_transport_chicago_crash_vehicles	Chicago DOT — vehicles involved in crashes
	us_transport_nyc_collisions	NYC Open Data / NYPD — motor vehicle collisions
	us_transport_nj_inspections	NJ MVC — vehicle inspection records
Traffic & Transit	us_transport_ny_aadt	NYSDOT — Annual Average Daily Traffic counts
	us_transport_ny_mta_bridge_tunnel	MTA — bridge and tunnel traffic volumes
	us_transport_ny_mta_subway	MTA — subway ridership by station
	us_transport_ny_ezpass	NY Thruway / MTA — E-ZPass usage data
	us_transport_ny_ticket_convictions	NY DMV — traffic ticket conviction records
	us_transport_ny_traffic_tickets	NY DMV — traffic tickets issued
Infrastructure	us_transport_fuel_tax	FHWA — state motor fuel tax data
	us_transport_highway_funding	FHWA — federal highway funding apportionments
	us_transport_hpms_county	FHWA HPMS — county-level road condition data
	us_transport_road_mileage	FHWA — national public road mileage by type
	us_transport_usdot_transit_uza	USDOT NTD — transit statistics by urbanized area
Registrations	us_transport_licensed_drivers	FHWA — licensed drivers by state/age
	us_transport_ny_driver_licenses	NY DMV — driver license records
	us_transport_ny_dmv_facilities	NY DMV — office locations and hours
	us_transport_ny_vehicle_reg	NY DMV — registered vehicle data
	us_transport_wa_ev_reg	WA DOL — electric vehicle registrations
	us_transport_ny_highway_mileage	NYSDOT — highway mileage by route type

Use cases

Fleet management & logistics — Query crash hotspots, AADT counts along delivery corridors, and toll/E-ZPass usage to optimize routing and assess infrastructure risk on specific road segments.

Insurance analytics — Pull NYC collision data, NJ inspection results, and NY traffic ticket convictions to enrich underwriting models with location- and vehicle-level safety signals.

Urban planning & research — Combine MTA subway ridership, bridge/tunnel volumes, and HPMS road data to analyze mobility patterns, identify capacity constraints, and model transit demand.

EV & sustainability analysis — Cross-reference Washington State EV registration growth against national fuel tax collections and highway funding data to track electrification trends and infrastructure investment.

Safety research — Join Chicago crash reports with NYC collision records and NY ticket conviction data to compare enforcement and outcome patterns across jurisdictions.

Input

Field	Type	Default	Description
searchTerms	string[]	—	Required. Keywords or location names (e.g. ["Manhattan", "I-95", "Brooklyn"]). Each term is searched across all enabled categories.
includeVehicleSafety	boolean	true	Crash reports (Chicago + NYC), NJ vehicle inspections.
includeTrafficData	boolean	true	AADT, MTA ridership, E-ZPass, traffic tickets/convictions.
includeInfrastructure	boolean	true	Fuel tax, highway funding, HPMS road data, road mileage, transit UZA stats.
includeRegistrations	boolean	false	Licensed drivers, NY/WA vehicle & driver registrations, NY DMV locations. Off by default (high volume).
maxResultsPerSource	integer	50	Rows returned per SIP product per term. Max 200 (gateway cap).
sipApiKey	string	—	Local testing only. Use the SIP_API_KEY environment variable on Apify.

Example input

{
  "searchTerms": ["Manhattan", "Brooklyn"],
  "includeVehicleSafety": true,
  "includeTrafficData": true,
  "includeInfrastructure": true,
  "includeRegistrations": false,
  "maxResultsPerSource": 50
}

Output (dataset items)

Each row is a raw SIP search hit with four Actor-added metadata fields:

Field	Description
_product_id	SIP product identifier (e.g. us_transport_nyc_collisions)
_source	Short label from the product map (e.g. nyc_collisions)
_search_term	The search term that produced this row
_collected_at	ISO 8601 UTC timestamp of when the row was collected

Native fields vary by product. Common examples include crash_date, borough, location, vehicle_type, injuries, road_name, aadt, station_id, ridership, registration_class, vin.

Example record (NYC collisions)

{
  "crash_date": "2024-03-15",
  "borough": "MANHATTAN",
  "on_street_name": "5 AVENUE",
  "number_of_persons_injured": 1,
  "number_of_persons_killed": 0,
  "contributing_factor_vehicle_1": "Driver Inattention/Distraction",
  "vehicle_type_code1": "Sedan",
  "latitude": "40.7549",
  "longitude": "-73.9840",
  "_product_id": "us_transport_nyc_collisions",
  "_source": "nyc_collisions",
  "_search_term": "Manhattan",
  "_collected_at": "2026-04-08T10:30:00Z"
}

Example record (MTA subway)

{
  "station": "TIMES SQ-42 ST",
  "line": "1 2 3",
  "ridership": 42891,
  "service_date": "2024-01-08",
  "_product_id": "us_transport_ny_mta_subway",
  "_source": "ny_mta_subway",
  "_search_term": "Manhattan",
  "_collected_at": "2026-04-08T10:30:00Z"
}

Configuration

Set the SIP gateway key as an Apify Actor environment variable (mark as secret):

Variable	Description
SIP_API_KEY	SIP X-API-Key value. Required.
SIP_API_BASE	Override gateway root (optional). Default: https://opendata.best/api/v1/data.

Never put the key in run input on production — use environment variables so keys are not stored in run history.

Pricing (reference)

Approximate positioning: ~$2 per 1,000 results (combined platform + API cost). Set exact USD amounts in the Apify Actor Pricing tab. This README does not lock prices.

Local development

cd "/Users/kane/Projects/Apify Actors/sip-us-transportation-search"
python3.13 -m venv .venv
.venv/bin/pip install -r requirements.txt
export SIP_API_KEY="your-key"
mkdir -p storage/key_value_stores/default
echo '{"searchTerms":["Manhattan"],"maxResultsPerSource":5}' > storage/key_value_stores/default/INPUT.json
apify run

Or run directly:

$SIP_API_KEY=your-key python -m src

(with INPUT.json under storage/key_value_stores/default/ per Apify CLI conventions).

Deploy

apify login
apify push

Use APIFY_TOKEN or CLI login — never commit tokens to git.

Legal

You must comply with SIP terms of use, Apify terms of service, and all applicable data protection and privacy laws (including CCPA for California driver data and any applicable DPPA restrictions on DMV records). This Actor is an API client to the SIP Public Data Gateway; you are responsible for the lawful use of all downstream government data. Driver and vehicle registration data may carry additional restrictions under the Driver's Privacy Protection Act (DPPA) — consult legal counsel before use in commercial applications.

Use as MCP Tool (AI Agent Integration)

This Actor works as an MCP tool — AI agents (Claude, GPT, Cursor) can discover and run it automatically.

Quick setup (Claude Desktop / Cursor / VS Code)

Add to your MCP config:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}

Then ask your AI: "Search for Tesla recall in US transportation databases"

Direct API call

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("lentic_clockss/us-transportation-search").call(
    run_input={"searchTerms": ["Tesla recall"], "maxResultsPerSource": 50}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Other Data API Actors

• EU Energy & Education Data API
• UK Government Data API
• Japan Government Data API

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🔗 Integrations

Connect this Actor to 1,000+ apps with zero code changes:

Platform	How to Connect
Make	Search "Apify" in Make → select "Run Actor" → Actor ID: lentic_clockss/us-transportation-search
n8n	Add Apify node → "Run Actor" action → Actor ID: lentic_clockss/us-transportation-search
Zapier	Use the Apify integration → "Run Actor" action
LangChain	See Python example below
MCP	Connect via npx @anthropic-ai/mcp apify → this Actor is auto-discoverable

Python (LangChain AI agent):

from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("lentic_clockss/us-transportation-search")
result = tool.invoke({"searchTerms": ["Tesla recall"], "includeVehicleSafety": True, "maxResultsPerSource": 5})

→ Browse all Actors: apify.com/lentic_clockss

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Also Available

• Postman Collection: Fork and test in Postman — pre-built requests with example responses
• GitHub: Collection source files — import JSON into any API client
• Direct API: https://opendata.best/api/v1/data — use with any HTTP client and your API key