The Location Library is a set of algorithms for location based analysis, including the following features:
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Primarily, the Location Library helps you with the following objectives:
The Location Library allows you to process information in the cloud for various use cases, including the following.
Vehicle sensors recognize traffic signs, such as stop and yield signs. With the Location Library, your application can infer the position of these traffic signs.
The traffic signs and their inferred positions can be communicated to a vehicle through the cloud in order to refresh the onboard map of the vehicle.
To help drivers avoid accidents, the Location Library allows you to feed information into notifications about safety issues ahead, such as:
Unexpected changes to the map, local hazard as listed above, or temporary closures can affect Highly Automated Driving systems. The Self-Healing Map feature notifies vehicles about such changes to the map, including real-time observations from vehicle sensors.
This feature allows you to provide navigation routes with the highest probability of available on-street parking near the destination. Drivers can save time when using these navigation routes as it is likely they find parking close to their destination.
The Location Library includes several modules.
location-corecontains interfaces and algorithms to process location data.
location-inmemorycontains efficient in-memory data structures that implement the core interfaces.
location-integration-optimized-mapcontains utilities to access the catalog Optimized Map for Location Library.
location-sparkprovides advanced distributed algorithms to be used specifically within Spark.
Before you start working with the Location Library, you should familiarize yourself with the following key concepts: