Passive Crowd-Sourced Map Updates via Location History Analysis
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Solution Overview
Problem
Personal Navigation Devices (PNDs) have outdated maps due to cumbersome traditional update mechanisms, and there is a need for a system that passively provides crowd-sourced map updates and alternate route recommendations with minimal user burden.
Innovation Solution
A system that tracks locations of mobile location-aware devices over time, analyzes user travel patterns to detect map updates and alternate routes, and provides these updates and recommendations to users and third-party map services, including calculating a degree of confidence for new road additions based on frequency and recency of use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mechanisms are used to update maps in PNDs, then map accuracy can be maintained, but the update process becomes cumbersome and inconvenient for users
Solution Approach 1:
The system enables map updates through passive crowd-sourcing where users' navigation devices automatically contribute to map improvements without manual intervention. The system self-updates by analyzing location data from multiple devices to detect new roads and route changes, eliminating the need for users to manually submit corrections while maintaining map accuracy.
Solution Approach 2:
The patent replaces manual mechanical map correction processes with automated electronic data analysis. Instead of requiring users to manually mark errors or submit corrections through interfaces, the system uses automated algorithms to process location histories, detect travel patterns, and identify map updates, substituting manual operations with electronic automation.
2Reliability
If manual map corrections are required from users, then map updates can be made, but user burden and complexity increase
Solution Approach 1:
The system performs self-service by automatically analyzing location data from navigation devices to detect and correct map errors. Users simply need to have their devices enabled for location tracking, and the system autonomously processes the data to identify new roads and route changes without requiring users to understand or interact with the update mechanism.
Solution Approach 2:
The patent introduces a central processing system as an intermediary between users' navigation devices and the map database. This intermediary collects location data, analyzes travel patterns, detects map updates, and communicates changes back to the system, shielding users from the complexity of the update process while ensuring accurate map maintenance.
3Ease of operation
If passive crowd-sourced location data is collected, then map updates can be made with minimal user burden, but data processing and analysis complexity increases
Solution Approach 1:
The system segments the data processing into distinct functional modules: location data collection from devices, travel pattern analysis, new road detection, and map update generation. This segmentation allows complex processing tasks to be divided into manageable steps that can be handled by specialized algorithms, reducing overall system complexity while maintaining ease of use.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors location data, detects patterns indicating map updates, and automatically applies corrections to the map database. This closed-loop feedback process ensures that map accuracy is maintained while the system handles the complexity of data processing autonomously without increasing user burden.
4Reliability
If traditional map update methods are used, then companies can control map data, but update speed and responsiveness decrease
Solution Approach 1:
The system maintains continuous operation by constantly collecting and analyzing location data from navigation devices in real-time. This continuous data stream enables the system to detect map updates as they occur and process them immediately, ensuring fast responsiveness while maintaining data accuracy through ongoing monitoring rather than periodic batch processing.
Solution Approach 2:
The patent performs preliminary data collection and analysis continuously in the background, preparing potential map updates before they are needed. The system pre-processes location data to identify patterns and detect new roads proactively, so when map updates are required, the information is already ready for immediate implementation, significantly improving update speed.
Data Source
AI summary
Systems and methods for providing passive crowd-sourced alternate route recommendations. In one embodiment, locations of users of a number of mobile location-aware devices are tracked over time. Upon receiving a request, users of mobile location-aware devices that have traveled from a desired start location to a desired stop location are identified. Location histories for the identified users are analyzed to determine one or more different routes taken from the desired start location to the desired stop location. The one or more different routes, or a select subset thereof, are then returned to the requestor as recommended alternate routes.