GPS Speed Variation Feature Vector for Road Attribute Prediction
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Solution Overview
Problem
Current GPS systems face challenges in accurately identifying and predicting attributes such as traffic lights, stop signs, speed bumps, and reduced speed zones along driving routes, relying on manual processing and outdated cartographic databases, which limits their effectiveness in real-time navigation and route optimization.
Innovation Solution
The system utilizes GPS elements to create a feature vector representing speed variations along a driving route, which is then input into a function to predict the presence of specific attributes like traffic lights, stop signs, or speed bumps, by analyzing sequences of GPS points and their topology, enabling improved route prediction and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processing is used to create and maintain cartographic databases, then the database can be updated with road changes, but the process is time-consuming and labor-intensive
Solution Approach 1:
The system enables automatic self-updating of cartographic databases by having vehicles collect GPS data and automatically process it to identify road network changes and attributes, eliminating the need for manual database maintenance while maintaining high accuracy
Solution Approach 2:
Manual mechanical processing of map updates is replaced with automated electronic GPS data collection and processing systems, where vehicles continuously gather location data that is automatically analyzed to update the database without human intervention
2Measurement precision
If GPS signals are collected and analyzed to detect attribute locations, then the topological structure of the road network can be refined, but the system complexity increases
Solution Approach 1:
The GPS system serves multiple functions simultaneously: it provides navigation guidance, collects data for database updates, detects road attributes like traffic lights and stop signs, and refines topological structure, thereby managing complexity through multi-functionality rather than separate specialized systems
Solution Approach 2:
A centralized server acts as an intermediary that receives GPS data from multiple vehicles, processes the information to identify attributes and update databases, and distributes updated information back to vehicles, thereby managing system complexity through centralized coordination rather than distributed complexity
3Measurement precision
If real-time GPS data is used to predict attributes along driving routes, then navigation accuracy is improved, but the computational requirements increase
Solution Approach 1:
The system pre-processes GPS data and pre-identifies attributes along potential routes before the vehicle reaches them, allowing the navigation system to make predictions about upcoming traffic lights, stop signs, and other attributes in advance, reducing real-time computational energy requirements while maintaining high accuracy
Data Source
AI summary
Various embodiments of the present invention provide systems, methods, and computer program products for identify the probability of a particular attribute being located along a segment of interest for a driving route. In general, various embodiments of the invention involve representing the segment of the driving route by patterns of speed variations obtained from GPS elements along the segment of the driving route and using the representation as input for functions representing various types of attributes to determine the probability of a particular type of attribute existing along the segment of the driving route.