# US Traffic Signal Locations & Intersection Dataset (`scholarstack/us-traffic-signal-extractor`) Actor
Download traffic signal locations for any US city or state — ~170k signalized intersections across 225 cities, all 50 states + DC. Signal type, ADA flags, approach count, nearest street. JSON/CSV/Excel/KML for SUMO, VISSIM, V2X. Data © OpenStreetMap contributors (ODbL 1.0).
- **URL**: https://apify.com/scholarstack/us-traffic-signal-extractor.md
- **Developed by:** [ScholarStack](https://apify.com/scholarstack) (community)
- **Categories:** Automation, Developer tools, Other
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $30.00 / 1,000 delivered intersections
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
Get **traffic signal locations** for any US city or state in minutes. This actor extracts **~170,000 signalized intersections** from OpenStreetMap across **225 cities in all 50 states + Washington, D.C.** — one clean, deduplicated record per intersection, classified by signal type, with approach-arm count, **ADA/accessibility flags**, nearest street, and confidence score. Export as JSON, CSV, Excel, or **KML for Google Earth**, ready for V2X/C-ITS, traffic simulation (SUMO/VISSIM), HD maps, and routing.
Run a free **`dryRun`** first to see the exact intersection count and estimated cost before paying.
*Need European coverage? Use the companion [Europe Traffic Signal Locations & Intersection Dataset](https://apify.com/scholarstack/traffic-signal-intersection-extractor) — same pipeline, 271 cities in 41 countries.*
*Los Angeles — full-city coverage (left) and the downtown road network with signalized intersections (right). Data © OpenStreetMap contributors, ODbL 1.0.*
### How to get traffic signal locations for any US city
1. Click **Try for free** and pick an input mode:
| Mode | How | Example |
|---|---|---|
| Single city | `city: "ca-socal-los_angeles"` | Los Angeles only |
| Multiple cities | `cities: ["wa-seattle", "ny-new_york"]` | Any combination |
| Whole state | `state: "WA"` | All listed Washington cities |
| Custom bbox | `customBbox: "34.00,-118.50,34.20,-118.20"` + `state: "CA-SOCAL"` | Any rectangle |
2. Set `dryRun: true` for a free estimate (count, cost, 10 sample records — no charge).
3. Run for real and download JSON, CSV, Excel, or KML from the Output tab.
### What data you get for each signalized intersection
| Field | Description |
|---|---|
| `intersection_id` | Stable, location-based ID `US-{STATE}-{CITY3}-{geohash8}` (e.g. `US-CA-SOCAL-LOS-9q5ctr1p`) |
| `state_code` | USPS state / region code (e.g. `WA`, `CA-NORCAL`, `CA-SOCAL`) |
| `city_slug` / `city_name` | City key and human-readable name |
| `lat` / `lon` | Intersection centroid (WGS84) |
| `osm_id` | A representative OSM node id for the intersection |
| `signal_type` | `vehicular_junction`, `pedestrian_crossing`, `vehicular_and_pedestrian`, `hawk_signal`, or `level_crossing` |
| `approach_count` | Number of road arms meeting at the junction (when available) |
| `nearest_street` | Name of the nearest named road |
| `accessibility` | ADA flags: `button_operated`, `sound_signal`, `tactile_paving`, `countdown_display`, `vibration_signal`, `bicycle_signal`, `leading_pedestrian_interval` (`true`/`false`/`null`) |
| `confidence` | `{ "score": 0.0–1.0, "reason": ... }` — Phase 1 is OSM-density based |
| `source_tier` | `osm` (Phase 2 will add `official+osm`) |
| `osm_last_edited` | When the signal was last edited in OSM |
| `data_vintage` | Date of the OSM data snapshot used |
| `attribution` | `© OpenStreetMap contributors, ODbL 1.0` |
#### Output example
```json
{
"intersection_id": "US-CA-SOCAL-LOS-9q5ctr1p",
"state_code": "CA-SOCAL",
"city_slug": "ca-socal-los_angeles",
"city_name": "Los Angeles",
"lat": 34.0522342,
"lon": -118.2436849,
"osm_id": 123456789,
"signal_type": "vehicular_junction",
"approach_count": 4,
"nearest_street": "Wilshire Blvd",
"accessibility": {
"button_operated": true,
"sound_signal": true,
"tactile_paving": true,
"countdown_display": null,
"vibration_signal": false,
"bicycle_signal": null,
"leading_pedestrian_interval": null
},
"source_tier": "osm",
"confidence": { "score": 0.8, "reason": "osm_only_dense_city" },
"osm_last_edited": "2024-05-05T20:14:00+00:00",
"data_vintage": "2026-06-04",
"source": "© OpenStreetMap contributors",
"license": "ODbL-1.0",
"attribution": "© OpenStreetMap contributors, ODbL 1.0"
}
````
### Signal types covered (vehicular, pedestrian, HAWK, level crossing)
| Value | Meaning |
|---|---|
| `vehicular_junction` | Road junction signal (`highway=traffic_signals`, no crossing) |
| `pedestrian_crossing` | Signalized pedestrian crossing (`crossing=traffic_signals`) |
| `vehicular_and_pedestrian` | Junction with a pedestrian phase |
| `hawk_signal` | HAWK pedestrian beacon (US-specific) |
| `level_crossing` | Railway level crossing with signals |
### Coverage: 225 cities, all 50 US states + DC
One major metro per state to start, with California split into **NorCal** and **SoCal** sub-regions (mirroring Geofabrik). Each region's signal data is sourced from the latest Geofabrik US-state OpenStreetMap extract. Run `dryRun: true` to see exact intersection counts and estimated cost for your city or state before paying.
### Export traffic signals to KML / Google Earth, CSV, or Excel
Every run produces **JSON** and **CSV**; **KML** export gives you a Google Earth-ready file with each signalized intersection as a placemark, and **Excel** export is available on the dataset. KML is the fastest way to visually verify coverage for your city before integrating the data.
### Using this data in SUMO, VISSIM, or V2X applications
Use `lat`/`lon` to match signalized junctions onto your SUMO or VISSIM network nodes, `approach_count` to sanity-check junction geometry, and `signal_type` to separate vehicular junctions from pedestrian crossings. For V2X/C-ITS work, the stable geohash-based `intersection_id` provides a persistent key for RSU placement planning and MAP/SPaT inventories across data refreshes. The ADA `accessibility` flags support pedestrian-accessibility audits and inclusive-routing applications.
### Key parameters
- **`signalType`** (default `["all"]`) — array; pick any taxonomy values or `all`.
- **`minConfidence`** (default `0`) — integer 0–100 (interpreted as 0.00–1.00); drops intersections below it.
- **`includeAccessibility`** (default `true`) — include the ADA flags block.
- **`clusterRadiusMeters`** (default `70`) — signals within this radius group into one intersection.
- **`mergeRadiusMeters`** (default `70`) — centroids within this radius merge (fixes divided-road duplicates).
- **`maxResults`** (default `1000`) — cap delivered/charged intersections. `0` = unlimited.
- **`dryRun`** (default `false`) — free estimate: count, cost, 10 sample records. No charge.
- **`priorDatasetId`** — Delta Mode; pass a previous run's `defaultDatasetId` to be charged only for added/removed/changed intersections.
### How much does it cost to extract traffic signal data?
**$0.03 per delivered intersection** ($30 per 1,000), plus $0.25 per run for KML export. Always run `dryRun: true` first to see the exact count and cost. For recurring refreshes, **Delta Mode** charges only for intersections that were added, removed, or changed since your last run — combined with Apify's scheduler, that turns this actor into a monthly **traffic signal change-monitoring feed** for your city or state.
### Data accuracy vs official city figures
Vehicular signalized-intersection counts from this actor track the figures published by city transportation departments within a few percent:
| City | Official DOT figure | This actor (vehicular only) | Difference |
|---|---|---|---|
| Los Angeles | ~4,850 (LADOT) | 4,856 | 0% |
| New York City | ~13,770 (NYC DOT) | 13,198 | −4% |
| Chicago | ~2,900 (CDOT) | 2,988 | +3% |
The default `signalType: ["all"]` additionally includes standalone **pedestrian-crossing** signals, so the all-types total per city is higher than the vehicular-only figure above. Set `signalType: ["vehicular_junction", "vehicular_and_pedestrian"]` to match a DOT's vehicular-intersection count.
### Data quality, confidence scores, and OSM attribution
- Data comes from **OpenStreetMap** (ODbL 1.0). Coverage and accuracy depend on OSM contributor activity in each city.
- `confidence.score` reflects OSM density for the city (Phase 1). Phase 2 will fuse official city open-data and raise confidence where the two agree.
- `osm_last_edited` is included per intersection so you can judge freshness yourself.
- Data is refreshed periodically from the latest Geofabrik US-state extracts.
Data © [OpenStreetMap contributors](https://www.openstreetmap.org/copyright), available under the [Open Database License (ODbL 1.0)](https://opendatacommons.org/licenses/odbl/). Any use of this data must credit OpenStreetMap contributors and comply with ODbL terms. Note for downstream use: datasets you build from this data are Derivative Databases under the ODbL — if you use them publicly, they must remain available under ODbL terms with OpenStreetMap attribution. Internal/private use carries no share-alike obligation.
### Disclaimer
This is an independent, unofficial tool built on publicly available OpenStreetMap data. It is not affiliated with or endorsed by the OpenStreetMap Foundation, Geofabrik, Google (Google Earth), the Eclipse Foundation (SUMO), or PTV Group (VISSIM). Product names are used solely to indicate data-format compatibility.
### FAQ
#### Where can I download traffic signal locations for a US city?
Run this actor with your city key (e.g. `wa-seattle`) and download every signalized intersection as JSON, CSV, Excel, or KML in minutes — no GIS tooling required. All 225 covered cities and 50 states work the same way.
#### Does OpenStreetMap have traffic signal data?
Yes — OSM maps signals as `highway=traffic_signals` and `crossing=traffic_signals` nodes, but raw nodes include multiple poles per junction. This actor clusters and deduplicates them into **one record per real intersection**, classified by signal type including US-specific HAWK beacons.
#### Can I get pedestrian signal and ADA accessibility data?
Yes — each record carries ADA flags (audible signals, tactile paving, push buttons, countdown displays, leading pedestrian intervals and more) where OSM contributors have mapped them.
#### Can I get the data as KML for Google Earth?
Yes — KML export ($0.25 per run) produces a Google Earth-ready file of all delivered intersections.
#### Can I monitor a city for new or changed signals?
Yes — Delta Mode (`priorDatasetId`) returns and charges only for added, removed, or changed intersections since your previous run. Schedule it monthly for a continuous change feed.
#### How is this different from the Europe version?
Same pipeline and schema family, different coverage: this actor covers 225 US cities across all 50 states with ADA/accessibility flags and the US signal taxonomy (incl. HAWK beacons); the [Europe actor](https://apify.com/scholarstack/traffic-signal-intersection-extractor) covers 271 cities in 41 countries.
# Actor input Schema
## `city` (type: `string`):
Select a single city (e.g. Los Angeles). Ignored if customBbox is set. For multiple cities use 'Cities' below; for all cities in a state use 'State'.
## `cities` (type: `array`):
Select multiple cities to process in one run. All results are delivered into a single dataset. Overrides 'City' if set. Ignored if 'State' or 'Custom bbox' is set.
## `state` (type: `string`):
Select a state to process ALL its cities in one run. Overrides 'City' and 'Cities' inputs. Ignored if 'Custom bbox' is set.
## `customBbox` (type: `string`):
Override everything with your own bbox: "south,west,north,east" in decimal degrees. Example: "34.00,-118.50,34.20,-118.20"
## `clusterRadiusMeters` (type: `integer`):
Signals within this radius are grouped into one intersection. Default 40m suits dense US grids (some downtown blocks are ~60m apart). Raise it (e.g. 70m) for sprawling suburbs with wide junctions.
## `mergeRadiusMeters` (type: `integer`):
Centroids within this radius of each other are merged into one intersection. Default 40m. Lower it if separate nearby junctions get merged; raise it if duplicate points appear at one wide multi-carriageway junction.
## `signalType` (type: `array`):
Filter by intersection signal type. Pick one or more, or 'All'. vehicular\_junction = road junctions; pedestrian\_crossing = crossings; vehicular\_and\_pedestrian = junction with a pedestrian phase; hawk\_signal = HAWK pedestrian beacon; level\_crossing = rail crossing.
## `minConfidence` (type: `integer`):
Drop intersections whose confidence score is below this value (0–100, interpreted as 0.00–1.00). 0 = keep all. Phase 1 scores are OSM-density based.
## `includeAccessibility` (type: `boolean`):
Include the ADA / accessibility block (button\_operated, sound\_signal, tactile\_paving, countdown\_display, …) in each output record.
## `wholeState` (type: `boolean`):
Process EVERY signalized intersection in the selected State's data, ignoring city selection. Use together with 'State'. Large output — run dryRun=true first to see the count and cost.
## `includeKml` (type: `boolean`):
Also produce a Google Earth / KML file of the delivered intersections (saved to the run's key-value store with a public URL). Off by default. Charged once per run as a flat KML-export fee — see Pricing.
## `maxResults` (type: `integer`):
Cap the total number of intersections delivered (and charged) across all cities. 0 = unlimited. Run dryRun=true first to see the full count.
## `dryRun` (type: `boolean`):
When true, runs the full pipeline but charges nothing and delivers nothing. Returns estimated count, estimated cost, and a 10-row sample.
## `priorDatasetId` (type: `string`):
The defaultDatasetId of a previous run of this actor for the same city/state. Find it in the run's Storage tab in Apify Console. When set, only added, removed, and changed intersections are charged.
## `kmlFromDatasetId` (type: `string`):
Forgot to enable KML on a previous run? Paste that run's defaultDatasetId (Storage tab) here and run again. The actor builds a KML from those exact results and charges ONLY the flat $0.25 KML fee — no re-extraction, no per-intersection charges. Leave empty for normal runs.
## Actor input object example
```json
{
"city": "ca-socal-los_angeles",
"clusterRadiusMeters": 40,
"mergeRadiusMeters": 40,
"signalType": [
"all"
],
"minConfidence": 0,
"includeAccessibility": true,
"wholeState": false,
"includeKml": false,
"maxResults": 1000,
"dryRun": false
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {};
// Run the Actor and wait for it to finish
const run = await client.actor("scholarstack/us-traffic-signal-extractor").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {}
# Run the Actor and wait for it to finish
run = client.actor("scholarstack/us-traffic-signal-extractor").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{}' |
apify call scholarstack/us-traffic-signal-extractor --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scholarstack/us-traffic-signal-extractor",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "US Traffic Signal Locations & Intersection Dataset",
"description": "Download traffic signal locations for any US city or state — ~170k signalized intersections across 225 cities, all 50 states + DC. Signal type, ADA flags, approach count, nearest street. JSON/CSV/Excel/KML for SUMO, VISSIM, V2X. Data © OpenStreetMap contributors (ODbL 1.0).",
"version": "1.0",
"x-build-id": "KYMUcYmDi50BGKCzC"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scholarstack~us-traffic-signal-extractor/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scholarstack-us-traffic-signal-extractor",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scholarstack~us-traffic-signal-extractor/runs": {
"post": {
"operationId": "runs-sync-scholarstack-us-traffic-signal-extractor",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scholarstack~us-traffic-signal-extractor/run-sync": {
"post": {
"operationId": "run-sync-scholarstack-us-traffic-signal-extractor",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"city": {
"title": "City (single)",
"enum": [
"al-birmingham",
"al-huntsville",
"al-mobile",
"al-montgomery",
"ak-anchorage",
"ak-fairbanks",
"ak-juneau",
"az-chandler",
"az-gilbert",
"az-glendale",
"az-mesa",
"az-phoenix",
"az-scottsdale",
"az-tucson",
"ar-fayetteville",
"ar-fort_smith",
"ar-little_rock",
"ca-norcal-fresno",
"ca-norcal-oakland",
"ca-norcal-sacramento",
"ca-norcal-san_francisco",
"ca-norcal-san_jose",
"ca-norcal-stockton",
"ca-socal-anaheim",
"ca-socal-bakersfield",
"ca-socal-chula_vista",
"ca-socal-irvine",
"ca-socal-long_beach",
"ca-socal-los_angeles",
"ca-socal-pasadena",
"ca-socal-riverside",
"ca-socal-san_diego",
"ca-socal-santa_ana",
"co-aurora",
"co-boulder",
"co-colorado_springs",
"co-denver",
"co-fort_collins",
"ct-bridgeport",
"ct-hartford",
"ct-new_haven",
"ct-stamford",
"de-dover",
"de-newark",
"de-wilmington",
"dc-washington",
"fl-fort_lauderdale",
"fl-jacksonville",
"fl-miami",
"fl-orlando",
"fl-st_petersburg",
"fl-tallahassee",
"fl-tampa",
"ga-athens",
"ga-atlanta",
"ga-augusta",
"ga-columbus",
"ga-savannah",
"hi-hilo",
"hi-honolulu",
"hi-kailua",
"id-boise",
"id-idaho_falls",
"id-meridian",
"id-nampa",
"il-aurora",
"il-chicago",
"il-naperville",
"il-peoria",
"il-rockford",
"il-springfield",
"in-bloomington",
"in-evansville",
"in-fort_wayne",
"in-indianapolis",
"in-south_bend",
"ia-cedar_rapids",
"ia-davenport",
"ia-des_moines",
"ia-iowa_city",
"ks-olathe",
"ks-overland_park",
"ks-topeka",
"ks-wichita",
"ky-bowling_green",
"ky-lexington",
"ky-louisville",
"la-baton_rouge",
"la-lafayette",
"la-new_orleans",
"la-shreveport",
"me-bangor",
"me-lewiston",
"me-portland",
"md-annapolis",
"md-baltimore",
"md-columbia",
"md-frederick",
"md-germantown",
"ma-boston",
"ma-cambridge",
"ma-lowell",
"ma-springfield",
"ma-worcester",
"mi-ann_arbor",
"mi-detroit",
"mi-flint",
"mi-grand_rapids",
"mi-lansing",
"mn-duluth",
"mn-minneapolis",
"mn-rochester",
"mn-saint_paul",
"ms-biloxi",
"ms-gulfport",
"ms-hattiesburg",
"ms-jackson",
"mo-columbia",
"mo-kansas_city",
"mo-saint_louis",
"mo-springfield",
"mt-billings",
"mt-bozeman",
"mt-great_falls",
"mt-missoula",
"ne-bellevue",
"ne-lincoln",
"ne-omaha",
"nv-carson_city",
"nv-henderson",
"nv-las_vegas",
"nv-reno",
"nh-concord",
"nh-manchester",
"nh-nashua",
"nj-camden",
"nj-jersey_city",
"nj-newark",
"nj-paterson",
"nj-trenton",
"nm-albuquerque",
"nm-las_cruces",
"nm-santa_fe",
"ny-albany",
"ny-buffalo",
"ny-new_york",
"ny-rochester",
"ny-syracuse",
"ny-yonkers",
"nc-asheville",
"nc-charlotte",
"nc-durham",
"nc-greensboro",
"nc-raleigh",
"nc-winston_salem",
"nd-bismarck",
"nd-fargo",
"nd-grand_forks",
"oh-akron",
"oh-cincinnati",
"oh-cleveland",
"oh-columbus",
"oh-dayton",
"oh-toledo",
"ok-norman",
"ok-oklahoma_city",
"ok-tulsa",
"or-bend",
"or-eugene",
"or-portland",
"or-salem",
"pa-allentown",
"pa-erie",
"pa-harrisburg",
"pa-philadelphia",
"pa-pittsburgh",
"ri-newport",
"ri-providence",
"ri-warwick",
"sc-charleston",
"sc-columbia",
"sc-greenville",
"sc-myrtle_beach",
"sd-pierre",
"sd-rapid_city",
"sd-sioux_falls",
"tn-chattanooga",
"tn-knoxville",
"tn-memphis",
"tn-nashville",
"tx-arlington",
"tx-austin",
"tx-dallas",
"tx-el_paso",
"tx-fort_worth",
"tx-houston",
"tx-lubbock",
"tx-san_antonio",
"ut-ogden",
"ut-provo",
"ut-salt_lake_city",
"ut-west_valley_city",
"vt-burlington",
"vt-montpelier",
"vt-rutland",
"va-alexandria",
"va-chesapeake",
"va-norfolk",
"va-richmond",
"va-virginia_beach",
"wa-bellevue",
"wa-seattle",
"wa-spokane",
"wa-tacoma",
"wa-vancouver",
"wv-charleston",
"wv-huntington",
"wv-morgantown",
"wi-green_bay",
"wi-kenosha",
"wi-madison",
"wi-milwaukee",
"wy-casper",
"wy-cheyenne",
"wy-laramie"
],
"type": "string",
"description": "Select a single city (e.g. Los Angeles). Ignored if customBbox is set. For multiple cities use 'Cities' below; for all cities in a state use 'State'.",
"default": "ca-socal-los_angeles"
},
"cities": {
"title": "Cities (batch — pick multiple)",
"type": "array",
"description": "Select multiple cities to process in one run. All results are delivered into a single dataset. Overrides 'City' if set. Ignored if 'State' or 'Custom bbox' is set.",
"items": {
"type": "string",
"enum": [
"al-birmingham",
"al-huntsville",
"al-mobile",
"al-montgomery",
"ak-anchorage",
"ak-fairbanks",
"ak-juneau",
"az-chandler",
"az-gilbert",
"az-glendale",
"az-mesa",
"az-phoenix",
"az-scottsdale",
"az-tucson",
"ar-fayetteville",
"ar-fort_smith",
"ar-little_rock",
"ca-norcal-fresno",
"ca-norcal-oakland",
"ca-norcal-sacramento",
"ca-norcal-san_francisco",
"ca-norcal-san_jose",
"ca-norcal-stockton",
"ca-socal-anaheim",
"ca-socal-bakersfield",
"ca-socal-chula_vista",
"ca-socal-irvine",
"ca-socal-long_beach",
"ca-socal-los_angeles",
"ca-socal-pasadena",
"ca-socal-riverside",
"ca-socal-san_diego",
"ca-socal-santa_ana",
"co-aurora",
"co-boulder",
"co-colorado_springs",
"co-denver",
"co-fort_collins",
"ct-bridgeport",
"ct-hartford",
"ct-new_haven",
"ct-stamford",
"de-dover",
"de-newark",
"de-wilmington",
"dc-washington",
"fl-fort_lauderdale",
"fl-jacksonville",
"fl-miami",
"fl-orlando",
"fl-st_petersburg",
"fl-tallahassee",
"fl-tampa",
"ga-athens",
"ga-atlanta",
"ga-augusta",
"ga-columbus",
"ga-savannah",
"hi-hilo",
"hi-honolulu",
"hi-kailua",
"id-boise",
"id-idaho_falls",
"id-meridian",
"id-nampa",
"il-aurora",
"il-chicago",
"il-naperville",
"il-peoria",
"il-rockford",
"il-springfield",
"in-bloomington",
"in-evansville",
"in-fort_wayne",
"in-indianapolis",
"in-south_bend",
"ia-cedar_rapids",
"ia-davenport",
"ia-des_moines",
"ia-iowa_city",
"ks-olathe",
"ks-overland_park",
"ks-topeka",
"ks-wichita",
"ky-bowling_green",
"ky-lexington",
"ky-louisville",
"la-baton_rouge",
"la-lafayette",
"la-new_orleans",
"la-shreveport",
"me-bangor",
"me-lewiston",
"me-portland",
"md-annapolis",
"md-baltimore",
"md-columbia",
"md-frederick",
"md-germantown",
"ma-boston",
"ma-cambridge",
"ma-lowell",
"ma-springfield",
"ma-worcester",
"mi-ann_arbor",
"mi-detroit",
"mi-flint",
"mi-grand_rapids",
"mi-lansing",
"mn-duluth",
"mn-minneapolis",
"mn-rochester",
"mn-saint_paul",
"ms-biloxi",
"ms-gulfport",
"ms-hattiesburg",
"ms-jackson",
"mo-columbia",
"mo-kansas_city",
"mo-saint_louis",
"mo-springfield",
"mt-billings",
"mt-bozeman",
"mt-great_falls",
"mt-missoula",
"ne-bellevue",
"ne-lincoln",
"ne-omaha",
"nv-carson_city",
"nv-henderson",
"nv-las_vegas",
"nv-reno",
"nh-concord",
"nh-manchester",
"nh-nashua",
"nj-camden",
"nj-jersey_city",
"nj-newark",
"nj-paterson",
"nj-trenton",
"nm-albuquerque",
"nm-las_cruces",
"nm-santa_fe",
"ny-albany",
"ny-buffalo",
"ny-new_york",
"ny-rochester",
"ny-syracuse",
"ny-yonkers",
"nc-asheville",
"nc-charlotte",
"nc-durham",
"nc-greensboro",
"nc-raleigh",
"nc-winston_salem",
"nd-bismarck",
"nd-fargo",
"nd-grand_forks",
"oh-akron",
"oh-cincinnati",
"oh-cleveland",
"oh-columbus",
"oh-dayton",
"oh-toledo",
"ok-norman",
"ok-oklahoma_city",
"ok-tulsa",
"or-bend",
"or-eugene",
"or-portland",
"or-salem",
"pa-allentown",
"pa-erie",
"pa-harrisburg",
"pa-philadelphia",
"pa-pittsburgh",
"ri-newport",
"ri-providence",
"ri-warwick",
"sc-charleston",
"sc-columbia",
"sc-greenville",
"sc-myrtle_beach",
"sd-pierre",
"sd-rapid_city",
"sd-sioux_falls",
"tn-chattanooga",
"tn-knoxville",
"tn-memphis",
"tn-nashville",
"tx-arlington",
"tx-austin",
"tx-dallas",
"tx-el_paso",
"tx-fort_worth",
"tx-houston",
"tx-lubbock",
"tx-san_antonio",
"ut-ogden",
"ut-provo",
"ut-salt_lake_city",
"ut-west_valley_city",
"vt-burlington",
"vt-montpelier",
"vt-rutland",
"va-alexandria",
"va-chesapeake",
"va-norfolk",
"va-richmond",
"va-virginia_beach",
"wa-bellevue",
"wa-seattle",
"wa-spokane",
"wa-tacoma",
"wa-vancouver",
"wv-charleston",
"wv-huntington",
"wv-morgantown",
"wi-green_bay",
"wi-kenosha",
"wi-madison",
"wi-milwaukee",
"wy-casper",
"wy-cheyenne",
"wy-laramie"
],
"enumTitles": [
"Birmingham (AL)",
"Huntsville (AL)",
"Mobile (AL)",
"Montgomery (AL)",
"Anchorage (AK)",
"Fairbanks (AK)",
"Juneau (AK)",
"Chandler (AZ)",
"Gilbert (AZ)",
"Glendale (AZ)",
"Mesa (AZ)",
"Phoenix (AZ)",
"Scottsdale (AZ)",
"Tucson (AZ)",
"Fayetteville (AR)",
"Fort Smith (AR)",
"Little Rock (AR)",
"Fresno (CA-NORCAL)",
"Oakland (CA-NORCAL)",
"Sacramento (CA-NORCAL)",
"San Francisco (CA-NORCAL)",
"San Jose (CA-NORCAL)",
"Stockton (CA-NORCAL)",
"Anaheim (CA-SOCAL)",
"Bakersfield (CA-SOCAL)",
"Chula Vista (CA-SOCAL)",
"Irvine (CA-SOCAL)",
"Long Beach (CA-SOCAL)",
"Los Angeles (CA-SOCAL)",
"Pasadena (CA-SOCAL)",
"Riverside (CA-SOCAL)",
"San Diego (CA-SOCAL)",
"Santa Ana (CA-SOCAL)",
"Aurora (CO)",
"Boulder (CO)",
"Colorado Springs (CO)",
"Denver (CO)",
"Fort Collins (CO)",
"Bridgeport (CT)",
"Hartford (CT)",
"New Haven (CT)",
"Stamford (CT)",
"Dover (DE)",
"Newark (DE)",
"Wilmington (DE)",
"Washington (DC)",
"Fort Lauderdale (FL)",
"Jacksonville (FL)",
"Miami (FL)",
"Orlando (FL)",
"St. Petersburg (FL)",
"Tallahassee (FL)",
"Tampa (FL)",
"Athens (GA)",
"Atlanta (GA)",
"Augusta (GA)",
"Columbus (GA)",
"Savannah (GA)",
"Hilo (HI)",
"Honolulu (HI)",
"Kailua (HI)",
"Boise (ID)",
"Idaho Falls (ID)",
"Meridian (ID)",
"Nampa (ID)",
"Aurora (IL)",
"Chicago (IL)",
"Naperville (IL)",
"Peoria (IL)",
"Rockford (IL)",
"Springfield (IL)",
"Bloomington (IN)",
"Evansville (IN)",
"Fort Wayne (IN)",
"Indianapolis (IN)",
"South Bend (IN)",
"Cedar Rapids (IA)",
"Davenport (IA)",
"Des Moines (IA)",
"Iowa City (IA)",
"Olathe (KS)",
"Overland Park (KS)",
"Topeka (KS)",
"Wichita (KS)",
"Bowling Green (KY)",
"Lexington (KY)",
"Louisville (KY)",
"Baton Rouge (LA)",
"Lafayette (LA)",
"New Orleans (LA)",
"Shreveport (LA)",
"Bangor (ME)",
"Lewiston (ME)",
"Portland (ME)",
"Annapolis (MD)",
"Baltimore (MD)",
"Columbia (MD)",
"Frederick (MD)",
"Germantown (MD)",
"Boston (MA)",
"Cambridge (MA)",
"Lowell (MA)",
"Springfield (MA)",
"Worcester (MA)",
"Ann Arbor (MI)",
"Detroit (MI)",
"Flint (MI)",
"Grand Rapids (MI)",
"Lansing (MI)",
"Duluth (MN)",
"Minneapolis (MN)",
"Rochester (MN)",
"Saint Paul (MN)",
"Biloxi (MS)",
"Gulfport (MS)",
"Hattiesburg (MS)",
"Jackson (MS)",
"Columbia (MO)",
"Kansas City (MO)",
"Saint Louis (MO)",
"Springfield (MO)",
"Billings (MT)",
"Bozeman (MT)",
"Great Falls (MT)",
"Missoula (MT)",
"Bellevue (NE)",
"Lincoln (NE)",
"Omaha (NE)",
"Carson City (NV)",
"Henderson (NV)",
"Las Vegas (NV)",
"Reno (NV)",
"Concord (NH)",
"Manchester (NH)",
"Nashua (NH)",
"Camden (NJ)",
"Jersey City (NJ)",
"Newark (NJ)",
"Paterson (NJ)",
"Trenton (NJ)",
"Albuquerque (NM)",
"Las Cruces (NM)",
"Santa Fe (NM)",
"Albany (NY)",
"Buffalo (NY)",
"New York City (NY)",
"Rochester (NY)",
"Syracuse (NY)",
"Yonkers (NY)",
"Asheville (NC)",
"Charlotte (NC)",
"Durham (NC)",
"Greensboro (NC)",
"Raleigh (NC)",
"Winston-Salem (NC)",
"Bismarck (ND)",
"Fargo (ND)",
"Grand Forks (ND)",
"Akron (OH)",
"Cincinnati (OH)",
"Cleveland (OH)",
"Columbus (OH)",
"Dayton (OH)",
"Toledo (OH)",
"Norman (OK)",
"Oklahoma City (OK)",
"Tulsa (OK)",
"Bend (OR)",
"Eugene (OR)",
"Portland (OR)",
"Salem (OR)",
"Allentown (PA)",
"Erie (PA)",
"Harrisburg (PA)",
"Philadelphia (PA)",
"Pittsburgh (PA)",
"Newport (RI)",
"Providence (RI)",
"Warwick (RI)",
"Charleston (SC)",
"Columbia (SC)",
"Greenville (SC)",
"Myrtle Beach (SC)",
"Pierre (SD)",
"Rapid City (SD)",
"Sioux Falls (SD)",
"Chattanooga (TN)",
"Knoxville (TN)",
"Memphis (TN)",
"Nashville (TN)",
"Arlington (TX)",
"Austin (TX)",
"Dallas (TX)",
"El Paso (TX)",
"Fort Worth (TX)",
"Houston (TX)",
"Lubbock (TX)",
"San Antonio (TX)",
"Ogden (UT)",
"Provo (UT)",
"Salt Lake City (UT)",
"West Valley City (UT)",
"Burlington (VT)",
"Montpelier (VT)",
"Rutland (VT)",
"Alexandria (VA)",
"Chesapeake (VA)",
"Norfolk (VA)",
"Richmond (VA)",
"Virginia Beach (VA)",
"Bellevue (WA)",
"Seattle (WA)",
"Spokane (WA)",
"Tacoma (WA)",
"Vancouver (WA)",
"Charleston (WV)",
"Huntington (WV)",
"Morgantown (WV)",
"Green Bay (WI)",
"Kenosha (WI)",
"Madison (WI)",
"Milwaukee (WI)",
"Casper (WY)",
"Cheyenne (WY)",
"Laramie (WY)"
]
}
},
"state": {
"title": "State (batch — all cities)",
"enum": [
"AK",
"AL",
"AR",
"AZ",
"CA-NORCAL",
"CA-SOCAL",
"CO",
"CT",
"DC",
"DE",
"FL",
"GA",
"HI",
"IA",
"ID",
"IL",
"IN",
"KS",
"KY",
"LA",
"MA",
"MD",
"ME",
"MI",
"MN",
"MO",
"MS",
"MT",
"NC",
"ND",
"NE",
"NH",
"NJ",
"NM",
"NV",
"NY",
"OH",
"OK",
"OR",
"PA",
"RI",
"SC",
"SD",
"TN",
"TX",
"UT",
"VA",
"VT",
"WA",
"WI",
"WV",
"WY"
],
"type": "string",
"description": "Select a state to process ALL its cities in one run. Overrides 'City' and 'Cities' inputs. Ignored if 'Custom bbox' is set."
},
"customBbox": {
"title": "Custom bounding box",
"type": "string",
"description": "Override everything with your own bbox: \"south,west,north,east\" in decimal degrees. Example: \"34.00,-118.50,34.20,-118.20\""
},
"clusterRadiusMeters": {
"title": "Cluster radius (metres)",
"minimum": 10,
"maximum": 150,
"type": "integer",
"description": "Signals within this radius are grouped into one intersection. Default 40m suits dense US grids (some downtown blocks are ~60m apart). Raise it (e.g. 70m) for sprawling suburbs with wide junctions.",
"default": 40
},
"mergeRadiusMeters": {
"title": "Merge radius (metres)",
"minimum": 10,
"maximum": 150,
"type": "integer",
"description": "Centroids within this radius of each other are merged into one intersection. Default 40m. Lower it if separate nearby junctions get merged; raise it if duplicate points appear at one wide multi-carriageway junction.",
"default": 40
},
"signalType": {
"title": "Signal type(s)",
"type": "array",
"description": "Filter by intersection signal type. Pick one or more, or 'All'. vehicular_junction = road junctions; pedestrian_crossing = crossings; vehicular_and_pedestrian = junction with a pedestrian phase; hawk_signal = HAWK pedestrian beacon; level_crossing = rail crossing.",
"items": {
"type": "string",
"enum": [
"all",
"vehicular_junction",
"pedestrian_crossing",
"vehicular_and_pedestrian",
"hawk_signal",
"level_crossing"
],
"enumTitles": [
"All signal types",
"Vehicular junction",
"Pedestrian crossing",
"Vehicular + pedestrian",
"HAWK signal",
"Level crossing"
]
},
"default": [
"all"
]
},
"minConfidence": {
"title": "Minimum confidence",
"minimum": 0,
"maximum": 100,
"type": "integer",
"description": "Drop intersections whose confidence score is below this value (0–100, interpreted as 0.00–1.00). 0 = keep all. Phase 1 scores are OSM-density based.",
"default": 0
},
"includeAccessibility": {
"title": "Include accessibility flags",
"type": "boolean",
"description": "Include the ADA / accessibility block (button_operated, sound_signal, tactile_paving, countdown_display, …) in each output record.",
"default": true
},
"wholeState": {
"title": "Whole state (ignore city)",
"type": "boolean",
"description": "Process EVERY signalized intersection in the selected State's data, ignoring city selection. Use together with 'State'. Large output — run dryRun=true first to see the count and cost.",
"default": false
},
"includeKml": {
"title": "Generate KML file (+$0.25 per run)",
"type": "boolean",
"description": "Also produce a Google Earth / KML file of the delivered intersections (saved to the run's key-value store with a public URL). Off by default. Charged once per run as a flat KML-export fee — see Pricing.",
"default": false
},
"maxResults": {
"title": "Max results",
"minimum": 0,
"type": "integer",
"description": "Cap the total number of intersections delivered (and charged) across all cities. 0 = unlimited. Run dryRun=true first to see the full count.",
"default": 1000
},
"dryRun": {
"title": "Dry run (free estimate)",
"type": "boolean",
"description": "When true, runs the full pipeline but charges nothing and delivers nothing. Returns estimated count, estimated cost, and a 10-row sample.",
"default": false
},
"priorDatasetId": {
"title": "Prior Dataset ID (Delta Mode)",
"type": "string",
"description": "The defaultDatasetId of a previous run of this actor for the same city/state. Find it in the run's Storage tab in Apify Console. When set, only added, removed, and changed intersections are charged."
},
"kmlFromDatasetId": {
"title": "KML from existing run (KML-only mode)",
"type": "string",
"description": "Forgot to enable KML on a previous run? Paste that run's defaultDatasetId (Storage tab) here and run again. The actor builds a KML from those exact results and charges ONLY the flat $0.25 KML fee — no re-extraction, no per-intersection charges. Leave empty for normal runs."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```