Driving Assistant System Adaptive Landmark Selection
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Solution Overview
Problem
Conventional landmark-based navigation systems fail to adapt to changes in landmarks over time, leading to confusion for drivers as the system may display outdated or incorrect landmarks, resulting in potential wrong turns or missed turns.
Innovation Solution
A driving assistant system that continuously receives image data from a camera, identifies candidate landmarks, and allows users to confirm and store these landmarks, enabling adaptive tracking of changes and personalized landmark selection, thereby improving route guidance by using user-specified and dynamically updated landmarks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional landmark-based navigation systems use pre-stored landmark data, then the system is simple to operate, but the system cannot adapt to changes in landmarks over time, leading to outdated information
Solution Approach 1:
The system enables users to autonomously update landmark data by capturing images with their mobile devices and submitting them to the server. This self-service approach allows the navigation system to adapt to landmark changes without requiring complex automated detection algorithms, thus improving adaptability while maintaining system simplicity
Solution Approach 2:
The system implements a feedback mechanism where user-submitted landmark images are processed and verified by the server, then integrated into the navigation database. This feedback loop ensures continuous updates of landmark information, allowing the system to adapt to environmental changes over time
2Measurement precision
If the system automatically displays landmarks without user confirmation, then the operation is fast and convenient, but the accuracy of landmark identification deteriorates
Solution Approach 1:
The system presents multiple candidate landmarks to the user rather than automatically selecting one, allowing the user to choose from several options. This partial action approach maintains operational convenience by limiting user input to simple selection while significantly improving landmark identification accuracy through user verification
Solution Approach 2:
The system introduces an intermediary verification step where the server processes and validates user-submitted landmark images before integrating them into the navigation database. This intermediary layer ensures accuracy by filtering and verifying landmark data while maintaining ease of operation through automated processing
3Reliability
If the system uses static landmark database updates, then the system is easy to maintain, but the landmark information becomes outdated over time
Solution Approach 1:
The system enables users to autonomously update landmark data by capturing images with their mobile devices and submitting them to the server. This self-service approach allows the navigation system to adapt to landmark changes without requiring complex automated detection algorithms, thus improving adaptability while maintaining system simplicity
Solution Approach 2:
The system continuously accepts and processes landmark update submissions from users, maintaining an ongoing process of data refreshment. This continuous action ensures landmark information remains current over time while distributing the maintenance effort across many users rather than requiring intensive centralized updates
Data Source
AI summary
Driving assistant systems and computer-implemented methods for improving landmark-based route guidance are provided. The computer-implemented method includes receiving, by a processor, image data including one or more landmarks. The computer-implemented method further includes identifying, by the processor, a candidate landmark within the image data. The computer-implemented method further includes presenting, by the processor, the candidate landmark to a user. The computer-implemented method further includes, in response to the user accepting the candidate landmark, storing, by the processor, the candidate landmark and a location of the candidate landmark.