Dynamic Navigation Modification via Crowd-Sourced Avoidance
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Solution Overview
Problem
Current vehicle navigation systems lack accurate data on road conditions such as potholes, flooding, and unpaved sections, which can make routes undesirable for travel, and often fail to provide effective alternatives for users trying to avoid these issues.
Innovation Solution
A system that allows users to designate areas of avoidance, which are then treated as impassable for route calculation, and utilizes crowd-sourced data to dynamically adjust route recommendations based on user behavior and conditions, enabling processors to receive and process user inputs and remote server updates to provide optimized route modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If navigation systems use standard traffic data and construction reports, then real-time traffic information is provided, but data accuracy and completeness about road conditions remain insufficient
Solution Approach 1:
The system enables users to self-report road conditions by designating areas of avoidance, allowing the navigation system to collect and utilize crowd-sourced data about actual road conditions such as potholes, flooding, and unpaved sections that official traffic data may not capture
Solution Approach 2:
The system implements feedback loops where user designations of areas to avoid are collected, processed, and used to update route calculations for all users, creating a continuous improvement cycle that enhances data accuracy over time through accumulated user experiences
2Adaptability or versatility
If users manually specify areas to avoid, then personalized route preferences are achieved, but system complexity and data processing requirements increase
Solution Approach 1:
The system creates a universal database of areas to avoid that serves all users, allowing individual customization without requiring separate processing for each user's preferences. The same crowd-sourced data benefits the entire user base, reducing overall system complexity
Solution Approach 2:
The system stores user designations in local memory as copies of area-of-avoidance data, allowing quick access and route calculations without repeatedly querying the full database or reprocessing raw data, thereby reducing computational complexity
3Measurement precision
If navigation systems treat designated areas as untravelable, then route avoidance accuracy improves, but available route options decrease
Solution Approach 1:
The system applies area-of-avoidance designations at the local level rather than globally, treating only specific geographic areas as untravelable while leaving the rest of the road network available. This allows precise avoidance of problematic sections without unnecessarily restricting overall route options
Solution Approach 2:
The system dynamically adjusts route calculations based on the vehicle's current location and the designated areas to avoid, providing real-time route modifications that maintain flexibility and offer multiple alternative paths when available
Data Source
AI summary
A system includes a processor configured to receive an instruction to avoid a user-identified route-portion. The processor is also configured to send the route-portion to a remote server. The processor is further configured to receive an updated recommendation relating to a size of the route-portion, responsive to the sending, and calculate a route avoiding the route-portion updated by the recommendation.