Lane-Level Traffic Guidance via Probe Data Segmentation
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Solution Overview
Problem
Current digital maps struggle to provide accurate, real-time lane-level traffic information due to limitations in processing power and periodic updates, leading to inefficient route optimization and incomplete traffic congestion feedback.
Innovation Solution
A method and system that utilize probe data from vehicles equipped with sensors to determine average speeds and travel times across multiple paths through intersections, calculating differential times to identify direction-based traffic events and provide lane-level traffic guidance, employing multi-modality detection and clustering algorithms to group road links and estimate consistent traffic patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dynamic computation of route optimization is performed using crowd-sourced traffic data, then route guidance accuracy is improved, but computational complexity and processing power requirements increase
Solution Approach 1:
The patent segments the road network into multiple road links and further divides each link into lane-level segments. Traffic data is collected and processed separately for each segment, allowing parallel computation and reducing the complexity of overall route optimization while maintaining high accuracy through granular data analysis
Solution Approach 2:
The patent introduces lane-level granularity as an additional dimension to traditional road segment traffic analysis. By adding this spatial dimension, the system achieves more precise traffic condition assessment and route optimization without proportionally increasing computational complexity, as the additional dimension organizes data in a structured manner that enables efficient processing
2Loss of information
If periodic updates of traffic data are implemented, then data freshness is improved, but update frequency and processing load increase
Solution Approach 1:
The patent merges traffic data from multiple sources including probe data from mobile devices, sensor data from road infrastructure, and historical traffic patterns into a unified processing framework. This consolidation allows the system to maintain fresh traffic information through coordinated updates rather than frequent independent updates of multiple data streams, reducing overall processing load while preserving data freshness
3Measurement precision
If lane-level traffic information is provided, then traffic congestion feedback precision is improved, but data processing requirements and system complexity increase
Solution Approach 1:
The patent segments road links into individual lane-level segments and collects traffic data separately for each lane. This segmentation enables precise traffic congestion feedback by analyzing conditions in each lane independently, while the modular structure of the segmentation approach allows for scalable implementation that manages system complexity through organized, reusable processing components
Solution Approach 2:
The patent applies local quality analysis by examining traffic conditions specifically for each lane rather than treating entire road links uniformly. This approach provides precise congestion feedback for specific lanes where it is most needed, while avoiding the complexity of analyzing every possible traffic parameter across the entire network, thus achieving high precision with manageable system complexity
Data Source
AI summary
A method, apparatus and computer program product are provided for establishing direction based traffic events and lane-level traffic associated therewith. Methods may include receiving a plurality of probe data points, where each probe data point includes location information associated with the respective probe apparatus; determining a path through an intersection from among a plurality of paths through the intersection for each probe apparatus based, at least in part, on a sequence of probe data points from each respective probe apparatus; determining, for each path through the intersection, an average speed of probe apparatuses traveling along the respective path and an average travel time along a road link approaching the intersection of the probe apparatuses traveling along the respective path; and determining a direction based traffic event in response to the differential amount of time between the highest average travel time and the lowest average travel time.