Navigation Device Inferred Path Feature Presentation
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Solution Overview
Problem
Existing GPS systems cannot provide users with path-based features without requiring them to define a route or destination, limiting the availability of valuable information such as upcoming climbs, hazards, and road conditions, especially in scenarios where users are not following a programmed route.
Innovation Solution
A computer-based method that determines a user's location and travel direction, infers a likely travel path, and analyzes mapping data to identify characteristics of interest, such as elevation data, to present relevant features to the user without the need for a defined route or destination, using transition costing logic and user preference information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If route-based features are implemented only when a defined route or destination is provided, then the accuracy and reliability of feature information is improved, but the availability and accessibility of these features to users deteriorates
Solution Approach 1:
The system performs preliminary route inference by analyzing historical location data and travel patterns before the user requests feature information. This allows the system to pre-calculate likely travel paths and associated features (climbs, hazards, road conditions) so that features are available immediately when users query them, without requiring users to explicitly define routes beforehand
Solution Approach 2:
The system automatically infers travel paths by analyzing the user's own historical location data and travel behavior patterns. This self-service approach allows the system to generate personalized route predictions without requiring external input from the user, thereby making features available while maintaining reliability through data-driven inference
2Adaptability or versatility
If the system infers travel paths using historical location data and travel patterns, then the availability of route-based features to users without defined routes is improved, but the complexity of the system increases
Solution Approach 1:
The system uses a unified travel pattern analysis module that serves multiple functions: inferring travel paths for feature presentation, predicting user destinations, and personalizing navigation preferences. This multi-functional approach consolidates what could be separate complex systems into a single versatile component, reducing overall system complexity while maintaining broad adaptability
Solution Approach 2:
The system creates simplified representations (copies) of travel patterns by analyzing historical location data and storing generalized route preferences. These copied patterns are then reused for inferring future travel paths, avoiding the need to perform complex real-time analysis for each query and thereby reducing computational complexity
3Ease of operation
If route-based features are presented based on inferred paths rather than defined routes, then the accessibility of features to casual users is improved, but the precision of feature information deteriorates
Solution Approach 1:
The system presents feature information for the most likely travel path with high confidence, while also providing optional information for alternative paths. This partial action approach ensures precise, actionable information is delivered first for the primary inferred route, while still offering broader coverage if users want to explore alternatives, thereby balancing precision with accessibility
Solution Approach 2:
The system applies different levels of precision to different portions of the inferred path. High-precision feature information is provided for segments with strong historical support and high confidence predictions, while lower-precision or probabilistic information is provided for less certain segments. This local differentiation maintains overall precision while enabling broad accessibility
Data Source
AI summary
A computer-based method is provided for providing analytical features at a navigation device. The method includes determining, by a position determining module of the navigation device, a first location of the navigation device associated with a first time. The method then proceeds to determine a second location of the navigation device associated with a second time and associates the first and second locations with coordinates on a first graph edge of a map, determines a travel direction based on a sequence of the locations, and determines a current location of the navigation device. An inferred path defining a travel path is then based on coordinates associated with the first and second locations, the travel direction, and the current location, and mapping data associated with the likely travel path is analyzed to identify a characteristic of interest of the likely travel path.


