Map Auto-Zoom Control for Road-Type-Aware Navigation Views
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Solution Overview
Problem
Users of connected computing systems face challenges in optimizing the presentation of map information for navigation, particularly in adjusting the zoom level based on road type and speed limits, which affects usability during travel.
Innovation Solution
A computing system that automatically adjusts the zoom level of a map based on the current road type and look ahead distance, using a control unit to determine the current road type and generate an appropriate zoom level for displaying the current location, even when speed limits are unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the map zoom level is manually adjusted to provide more map information, then the user can see more of the surrounding area, but the user cannot simultaneously optimize for both detailed navigation guidance and broader situational awareness
Solution Approach 1:
The patent implements dynamic zoom level adjustment based on real-time road type detection and speed limit data. The system automatically transitions between different zoom levels (e.g., from detailed street-level views to broader highway-level views) as the vehicle moves through different road environments, providing optimal map information presentation without requiring manual user intervention.
Solution Approach 2:
The system changes the map display parameter (zoom level) based on varying operational conditions such as road type (highway, urban, rural) and speed limit. By detecting these parameters and automatically adjusting the zoom level accordingly, the system optimizes both information presentation and usability for different driving contexts.
2Measurement precision
If the map displays detailed information for low-speed urban roads, then navigation accuracy is improved, but the map view becomes insufficient for high-speed highway navigation where broader context is needed
Solution Approach 1:
The patent applies different map display qualities (zoom levels) to different road types. Urban streets receive detailed, high-zoom presentations for precise navigation, while highways receive lower-zoom presentations that provide broader contextual information. This local quality adjustment ensures each road type receives the appropriate level of detail for its specific navigation needs.
Solution Approach 2:
The system dynamically changes the map zoom level parameter based on detected road type and speed limit conditions. This parameter adaptation allows the same navigation system to provide both high-precision urban navigation and broad-context highway navigation, resolving the contradiction between navigation accuracy and adaptability.
3Ease of operation
If the system requires manual user adjustment of map zoom level, then user control is maximized, but user burden and distraction during driving increases
Solution Approach 1:
The system performs self-service by automatically detecting road type, determining appropriate speed limits, and adjusting map zoom levels without requiring user input or manual control. This automation reduces user burden and distraction while maintaining optimal map presentation, as the system serves itself by making intelligent adjustments based on environmental conditions.
Solution Approach 2:
The system implements a feedback loop where it continuously monitors road type and speed limit conditions, automatically adjusts the map zoom level in response to these conditions, and maintains optimal presentation. This closed-loop control provides both automation benefits and adaptive responsiveness without requiring manual user intervention.
Data Source
AI summary
A system and method of operation of a computing system comprising: determining a current road type for a current road segment based on a current location located along the current road segment; generating a current zoom level of a map including the current location on the current road segment based on the current road type; generating a camera view of the map based on a look ahead distance for the current road type; and communicating the current zoom level for displaying the current location along the current road segment.