Uber Cars Nearby Scraper
Under maintenancePricing
from $1.00 / 1,000 results
Uber Cars Nearby Scraper
Under maintenanceGeospatial extraction tool designed to surface real-time vehicle positioning data from Uber's web application layer. Map the active supply of nearby drivers, providing invaluable metadata such as vehicle orientation, estimated times of arrival (ETA), and dispatch types.
Pricing
from $1.00 / 1,000 results
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0.0
(0)
Developer
SASWAVE
Maintained by CommunityActor stats
1
Bookmarked
6
Total users
3
Monthly active users
2 months ago
Last modified
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Uber Nearby Cars Scraper
The Uber Nearby Cars Scraper is a high-precision geospatial extraction tool designed to surface real-time vehicle positioning data from Uber's web application layer.
By passing specific latitude and longitude coordinates, the scraper maps the active supply of nearby drivers, providing invaluable metadata such as vehicle orientation, estimated times of arrival (ETA), and dispatch types.
FEATURE
Precise Vehicle Positioning: Extract exact coordinate positions (latitude and longitude) of active cars circling a target location.
Orientation & Heading Tracking: Capture the vehicle's bearing angle (0° to 360°) to determine which direction the car is facing or traveling.
Live Hyper-Local ETAs: Retrieve instant proximity calculations (etaInMin and etaStringShort) to measure immediate driver availability.
Vehicle Tier Mapping: Identify vehicle classifications through internal type IDs and secure cloud-hosted vehicle marker icons (mapImageUrl).
USE CASES
Supply & Demand Analytics: Track driver density across different municipal zones or pickup points at varying hours to calculate historical supply trends.
Dynamic Competitive Intelligence: Compare Uber's hyper-local vehicle availability and response times directly against alternative ride-hailing applications.
Smart City & Traffic Analysis: Monitor real-time fleet movement patterns in major urban bottlenecks to study congestion or spatial distribution.
Real Estate Proximity Auditing: Evaluate the "commute score" or transit convenience of properties by calculating average Uber response times at those locations throughout the week.
Automated Dispatch Optimization: Build predictive dashboards that notify field teams of the optimal moments to step outside based on immediate vehicle density.
OUTPUT
{"bearing": 316,"coordinate": {"latitude": 48.85504,"longitude": 2.3419,"__typename": "RVWebCommonCoordinate"},"etaInMin": 4,"etaStringShort": "4 mins","id": 35,"mapImageUrl": "https://d1a3f4spazzrp4.cloudfront.net/car-types/mapIconsStandard/car_bag_x_2d.png","__typename": "RVWebCommonVehicle"}
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