Familiarity-Annotated Search Suggestions for Landmark Navigation
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Solution Overview
Problem
Existing navigation systems struggle to provide effective navigation directions using landmarks that are familiar to the user, as the number of well-known landmarks is limited, and street signage can be poor, making it difficult for drivers to accurately judge distances and see signs.
Innovation Solution
A personalized map data generation system that utilizes a user's location history to identify and prioritize landmarks based on frequency and recency of visits, incorporating these landmarks into navigation instructions and search results to provide a frame of reference for the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional navigation directions using street names and building numbers are used, then the system can provide standardized navigation instructions, but drivers have difficulty accurately judging distance and seeing street signs, especially in areas with poor signage
Solution Approach 1:
The system transitions from generic navigation instructions to personalized landmark-based instructions tailored to each user's local environment. By selecting landmarks from the user's location history that are most familiar to them, the system provides locally-relevant references that improve both ease of operation and accuracy of distance judgment for that specific user.
Solution Approach 2:
The system leverages the user's own location history and familiar landmarks to provide navigation assistance. Instead of relying on external reference systems that may be unfamiliar to the user, the system uses the user's personal spatial memory and familiar references to guide them, making the navigation system serve the user's own needs and knowledge base.
2Adaptability or versatility
If the system uses well-known public landmarks for navigation, then landmarks are easily recognizable, but the number of available landmarks is limited
Solution Approach 1:
The system performs preliminary action by collecting and storing location history data before the user needs navigation assistance. By pre-processing and organizing the user's past location data to identify familiar landmarks, the system builds a personalized landmark database in advance that can be quickly retrieved and used for navigation when needed.
Solution Approach 2:
The system changes the parameter of landmark selection from using universally-known landmarks to using individually-familiar landmarks based on user-specific parameters from location history. This parameter change enables the system to expand the effective number of usable landmarks from a fixed set of public landmarks to a dynamic set personalized to each user's experiences and preferences.
3Measurement precision
If the system provides detailed turn-by-turn navigation instructions, then navigation precision is improved, but the number of instructions increases, reducing efficiency
Solution Approach 1:
The system extracts the essential navigation information by selecting only the most relevant landmarks from the user's location history that provide the necessary spatial references. Instead of providing exhaustive turn-by-turn instructions, the system extracts and presents only the critical landmark-based guidance needed for effective navigation, reducing the total number of instructions while maintaining precision.
Solution Approach 2:
The system applies partial action by providing navigation instructions only at key decision points where landmarks are most useful, rather than continuously providing detailed instructions throughout the entire journey. This selective approach maintains navigation precision at critical moments while improving overall efficiency by reducing unnecessary instructional overhead.
Data Source
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AI summary
To provide personalized data for display on a map, a server device obtains location data for a user and identifies locations that are familiar to the user based on the frequency and recency in which the user visits the locations. The server device then provides the familiar locations in search results/suggestions and annotates the familiar locations with a description of a relationship between the familiar location and the user. The server device also includes the familiar locations as landmarks for performing maneuvers in a set of navigation instructions. Furthermore, the server device provides a familiar location as a frame of reference on a map display when a user selects another location nearby the familiar location. Moreover, the server device includes a familiar location as an intermediate destination when the user request navigation directions to a final destination.