Progressive Map Maintenance for Mobile Navigation Units
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Solution Overview
Problem
Conventional systems for updating and refreshing maps in vehicles are resource-intensive, costly, and inefficient, as they transmit high levels of detail uniformly without considering user behavior, data availability, or bandwidth conditions, leading to expensive and cumbersome map data transmission.
Innovation Solution
The implementation of a progressive coding algorithm that prioritizes critical map elements, combines periodic pre-loads with on-demand updates, and utilizes a hybrid, multi-path connectivity arrangement to schedule transmissions over different communication channels based on importance and availability, optimizing data transmission according to user behavior and resource scarcity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If high-resolution map data is transmitted uniformly to all vehicles, then mapping detail and information availability are improved, but data transmission cost and bandwidth usage increase
Solution Approach 1:
The patent applies local quality by transmitting different levels of map data detail to different vehicles based on their specific needs. Critical map elements (roads, intersections, navigation routes) are transmitted with high detail, while non-critical elements (landmarks, points of interest) are transmitted with lower detail or delayed transmission, optimizing bandwidth usage while maintaining navigation functionality.
Solution Approach 2:
The patent segments map data into critical and non-critical elements, and further divides updates into periodic pre-loads and on-demand refreshes. This segmentation allows the system to prioritize transmission of essential navigation data while deferring or reducing transmission of supplementary information, thereby reducing overall data transmission costs.
2Loss of information
If high-resolution map data is transmitted to all vehicles, then mapping detail is improved, but communication-network bandwidth requirements increase
Solution Approach 1:
The system transmits high-detail map data only to vehicles that require it for navigation, while providing reduced-detail or placeholder data to other vehicles. This localized quality approach ensures that bandwidth is consumed only where necessary for maintaining mapping detail.
Solution Approach 2:
The patent implements partial action by transmitting only the necessary portion of map data to each vehicle based on its navigation needs. Rather than transmitting complete high-resolution datasets to all vehicles, the system transmits partial datasets containing only critical elements required for current navigation tasks.
3Loss of information
If map data is transmitted without considering user behavior or bandwidth conditions, then data availability is improved, but transmission efficiency deteriorates
Solution Approach 1:
The patent implements dynamic transmission strategies that adapt to changing bandwidth conditions and user behavior patterns. The system monitors network conditions and adjusts transmission timing, data selection, and compression levels in real-time, optimizing transmission efficiency while ensuring data availability when needed.
Solution Approach 2:
The system uses feedback from bandwidth conditions and user behavior analysis to adjust transmission decisions. By monitoring whether users actually access and utilize transmitted map data, the system refines its transmission strategy to prioritize data that provides real value, improving both availability and efficiency.
Data Source
AI summary
A system configured to receive baseline map data from a remote map-data source, and determine whether the baseline map data is sufficient for present mobile navigation-unit function, yielding a map-sufficiency determination. If the map-sufficiency determination is affirmative, using the baseline map data for the present mobile navigation-unit function. If the map-sufficiency determination is negative, the system predicts navigation-unit movement, obtains based on the navigation-unit movement predicted, supplemental map data, and uses the baseline map data and the supplemental map data for the present mobile navigation-unit function.