Traffic Prediction Model Using Link Patterns for Accurate ETA
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Solution Overview
Problem
Existing navigation systems often experience discrepancies between estimated and actual time of arrival due to inaccuracies in using real-time traffic information.
Innovation Solution
A method and system that combines previously-generated traffic pattern data with real-time traffic information to reduce error by selecting traffic pattern data with minimum speed error per link, utilizing a traffic prediction model to generate accurate traffic information, including estimated time of arrival.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only real-time traffic information is used to calculate estimated time of arrival, then the calculation process is simple, but the accuracy of estimated time of arrival deteriorates due to frequent discrepancies between actual and estimated arrival times
Solution Approach 1:
The patent combines multiple data sources including historical traffic pattern data and real-time traffic information into a unified processing system. The server integrates pattern speeds from historical data with real-time driving speeds, merging them into composite traffic information that improves estimation accuracy while managing complexity through systematic integration
2Measurement precision
If multiple traffic pattern data are processed to reduce error, then the accuracy of estimated time of arrival is improved, but the computational complexity increases
Solution Approach 1:
The system performs preliminary processing of historical traffic data to generate pre-computed pattern speeds before real-time prediction is needed. By pre-processing and storing traffic patterns in advance, the system reduces the computational burden during real-time operation while maintaining high prediction accuracy through the use of pre-analyzed traffic patterns
3Loss of information
If traffic volume of adjacent tiles is calculated and integrated, then the comprehensiveness of traffic information is improved, but the data processing complexity increases
Solution Approach 1:
The patent divides the geographic area into discrete tiles and processes traffic information for each tile independently. By segmenting the spatial domain into manageable units and calculating traffic volumes for adjacent tiles separately, the system comprehensively captures spatial traffic patterns while reducing overall processing complexity through modular, tile-based computation
Data Source
AI summary
Traffic information providing methods and systems are described. According to one embodiment, the traffic information providing method includes inputting previously-generated multiple traffic pattern data and real-time traffic information into a traffic prediction model, outputting an error at a first time point for each of the previously-generated multiple traffic pattern data, and generating traffic information from a departure point to a destination using first traffic pattern data having a minimum error among the previously-generated multiple traffic pattern data, wherein each of the multiple traffic pattern data is a combination of pattern speeds per link, which is a minimum unit of a road.