Destination Prediction Using Real-Time Travel Path Analysis
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Solution Overview
Problem
Current navigation systems require users to manually set their destination, which is cumbersome and often not used when traveling to familiar locations, missing opportunities for providing relevant information like traffic updates and points of interest.
Innovation Solution
A method and apparatus that predict a user's current travel path by generating real-time data and using historic travel data to determine potential destinations, weighting them based on distance and past visits, to provide personalized and contextual journey management without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If navigation systems are used for familiar destinations, then relevant information (traffic, POI) can be provided, but the system requires manual destination input which is cumbersome
Solution Approach 1:
The system automatically detects the driver's intended destination by analyzing GPS trajectory data without requiring manual input. The server receives location data, determines the current travel path, identifies the destination, and provides relevant information automatically, allowing the system to serve itself rather than requiring user operation.
Solution Approach 2:
The system performs preliminary destination identification and information preparation before the driver actually arrives at the destination. By continuously analyzing the travel path and predicting the destination in advance, the system can prepare and provide relevant traffic information and points of interest proactively.
2Ease of operation
If navigation systems are not used for familiar destinations, then manual input is avoided, but relevant information (traffic, POI) is not provided to the driver
Solution Approach 1:
The system automatically detects the driver's intended destination by analyzing GPS trajectory data without requiring manual input. The server receives location data, determines the current travel path, identifies the destination, and provides relevant information automatically, allowing the system to serve itself rather than requiring user operation.
3Adaptability or versatility
If destination prediction is implemented, then personalized journey management is achieved, but system complexity increases
Solution Approach 1:
The system introduces a server as an intermediary between the driver's device and the destination information database. The server receives location data, performs destination prediction using travel path analysis, and returns results, distributing the computational complexity across the network infrastructure rather than concentrating it in the driver's device.
Data Source
AI summary
The present disclosure relates to predicting a destination of a user's current travel path. Real-time travel data associated with the current travel path is generated, wherein the real-time travel data comprises the user's current location. A plurality of potential destinations of the current travel path are determined based on historic travel data associated with one or more historic travel paths of the user. At least one destination of the current travel path is predicted from the plurality of potential destinations based on tracking a distance from the user's current location to each of the plurality of potential destinations.