Lane-Level Route Guidance Using Probe Data Clustering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional digital maps provide limited specificity in route guidance, mainly relying on crowd-sourced traffic data that does not account for lane-level variations, which can lead to inefficiencies and safety issues in navigation, especially for autonomous vehicles.
Innovation Solution
The method involves processing circuitry that maps probe data to individual lanes, applies clustering algorithms to determine popular, efficient, or safe lane-level maneuver patterns, and generates route guidance based on these patterns, considering factors like time of day and weather conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If crowd-sourced traffic data is used for route guidance, then traffic information coverage is improved, but lane-level guidance specificity deteriorates
Solution Approach 1:
The patent segments the road network into individual lanes and further into lane segments, allowing probe data to be associated with specific lane segments rather than entire roadways. This segmentation enables the system to provide lane-level guidance while utilizing crowd-sourced data from multiple vehicles, resolving the contradiction between data coverage and guidance specificity.
2Measurement precision
If lane-level map matching is implemented, then navigation accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent applies local quality by creating detailed lane-level representations only where needed for navigation accuracy, rather than uniformly processing all road segments at the same level of detail. The system matches probe data to lane segments based on local geometric characteristics and traffic patterns, improving navigation accuracy while managing processing complexity through selective detail application.
3Reliability
If clustering algorithms are applied to determine maneuver patterns, then route guidance reliability is improved, but computational requirements increase
Solution Approach 1:
The patent applies partial action by using clustering algorithms selectively to identify dominant maneuver patterns rather than processing all possible lane change sequences. The system clusters probe data to find the most common maneuver patterns for each lane segment, providing reliable guidance based on predominant behaviors without the computational overhead of analyzing every possible maneuver combination.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method is provided for establishing determining lane-level route guidance, and more particularly, to establishing recommended lane-level guidance between an origin and a destination based on a safe, efficient, or popular path. Methods may include receiving a plurality of probe data points from a plurality of probe apparatuses, each probe apparatus traveling between a respective origin and destination pair; determining a lane-level maneuver pattern for each probe apparatus between the origin and the destination; providing for storage of the lane-level maneuver patterns for each probe apparatus in the memory; grouping together lane-level maneuver patterns for probe apparatuses having an origin and destination pair within a predefined similarity of origin and destination pairs of other apparatuses; and generating a lane-level maneuver pattern for each group based on at least one of a popularity, efficiency, or relatively safe lane-level maneuver pattern for the respective group.