Lane-Level Traffic Prediction in Geographic Databases
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Solution Overview
Problem
Current digital maps for autonomous vehicles and advanced driver-assistance systems lack lane-level traffic information, especially when network connections are unavailable or bandwidth is limited, making it difficult to provide accurate navigation functions.
Innovation Solution
The method involves generating and incorporating lane direction patterns, divergent parameter patterns, and lane event patterns into a digital map or geographic database, allowing vehicles to predict traffic conditions and travel times even without real-time data by analyzing probe information from vehicle apparatuses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lane-level traffic information is provided in real-time through network connection, then navigation accuracy is improved, but network bandwidth consumption increases and reliability decreases when network is unavailable
Solution Approach 1:
The patent pre-calculates and stores traffic parameter predictions (travel time, speed, traffic flow) for different epochs and road segments in the geographic database before network disconnection occurs. This preliminary action ensures that navigation functions can continue with accurate lane-level traffic information even when the network is unavailable, resolving the contradiction between real-time accuracy and offline reliability.
Solution Approach 2:
The patent generates lane-specific traffic parameter predictions for different road segments and epochs, storing differentiated data for each lane direction and time period. This local quality approach ensures that each lane receives customized traffic predictions tailored to its specific traffic patterns, improving navigation accuracy while optimizing network bandwidth by only transmitting necessary lane-level data.
2Measurement precision
If lane-level traffic information is provided with high detail, then navigation function accuracy is improved, but network bandwidth requirements increase
Solution Approach 1:
The patent extracts only the essential traffic parameters (travel time, speed, traffic flow) needed for navigation decisions and stores them in a condensed format in the geographic database. By taking out only the critical lane-level attributes rather than transmitting complete real-time traffic data streams, the system achieves high navigation accuracy while significantly reducing network bandwidth consumption.
Solution Approach 2:
The system pre-computes and stores aggregated traffic statistics for different epochs and road segments before they are needed for navigation. This preliminary aggregation reduces the data volume that needs to be transmitted over the network, as the database already contains processed lane-level traffic parameters ready for immediate use during offline navigation.
3Measurement precision
If real-time probe data is collected from multiple vehicles, then traffic prediction accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent merges probe data from multiple vehicles traveling on the same road segment and epoch to generate aggregated lane direction patterns, divergent parameter patterns, and lane event patterns. By combining data from multiple sources into unified traffic parameter predictions, the system improves prediction accuracy while reducing individual vehicle's data processing burden, as the heavy lifting is done collectively and results are stored in the geographic database for all to use.
Data Source
AI summary
A plurality of sequences of instances of probe data are received. Each sequence corresponds to travel of a vehicle apparatus along a first segment to one of two or more possible subsequent second segments and comprises an indication of at least one parameter characterizing the travel of the vehicle apparatus along the first segment. Groups of sequences are determined. Each group corresponds to a subsequent second segment. For a first group, at least one representative parameter is determined based on the at least one parameter of the sequences of the first group. An element of a data structure is modified and/or updated with the at least one representative parameter. The element of the data structure corresponds to the first group. A geographic database comprises the data structure and a navigation application is configured to use at least a portion of the data structure to perform a navigation function.