The Location Library is a set of algorithms for location based analysis, including the following features:
- Navigating a road network using graph abstractions
- Using property maps to access road attributes
- Searching for elements using geospatial queries (limited)
- Map matching recorded trips from car sensors or GPS devices to a road network
For the terms and conditions covering this documentation, see the HERE Documentation License.
Data privacy is of fundamental importance to HERE and our customers. We practice data minimization and don’t collect data we don’t need. And we promote pseudonymity for data subjects wherever a service does not require personal information to function. We employ privacy by design in services we develop. We strive to go beyond mere regulatory compliance and make privacy an integral part of our corporate culture. We believe that our approach to privacy is vital to earning and retaining the trust of our customers – and the bedrock of our future success as a data-driven location platform.
For more information on how data privacy is of fundamental importance to HERE and our customers, see the HERE Privacy Charter.
For more information on HERE data security and durability best practices, see the Data API.
Why Use the Location Library
Primarily, the Location Library helps you with the following objectives:
- Efficiently develop prototypes of location based algorithms and prove the feasibility of use cases, for example in conjunction with the Jupyter notebook
- Create location based programs that run in the HERE Workspace batch/stream pipelines
The Location Library allows you to process information in the cloud for various use cases, including the following.
Traffic Sign Recognition
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.
Local Hazard Warning
To help drivers avoid accidents, the Location Library allows you to feed information into notifications about safety issues ahead, such as:
- Disabled vehicles in the road
- Real-time hazard observations from vehicle sensors
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-core contains interfaces and algorithms to process location data.
location-inmemory contains efficient in-memory data structures that implement the core interfaces.
location-integration-optimized-map contains utilities to access the catalog Optimized Map for Location Library.
location-spark provides 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: