Lane-Level Traffic Data Determination Using Vehicle Sensor Distances
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Solution Overview
Problem
Conventional traffic data systems provide information only at the road or link level, failing to account for variations in traffic conditions across different lanes, which leads to inefficient and inaccurate navigation services, especially affecting autonomous vehicles.
Innovation Solution
A system and method for generating lane-level traffic data by determining average distances between vehicles in each lane, using sensor data from vehicles to provide real-time lane-level traffic conditions and navigation instructions, enabling better traffic management and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If road or link-level traffic data is used, then navigation services can be provided with basic traffic information, but the accuracy and efficiency of navigation services deteriorates due to inability to account for lane-level traffic variations
Solution Approach 1:
The patent segments traffic data processing from road-level to link-level to lane-level hierarchy. Traffic data is first aggregated at road level, then divided into link segments, and finally segmented into individual lanes for precise traffic condition assessment. This segmentation enables accurate lane-level navigation while managing computational complexity through hierarchical processing.
Solution Approach 2:
The patent applies local quality by providing differentiated traffic information for each lane rather than uniform road-level data. Each lane receives customized traffic conditions, vehicle density, and speed data specific to its local characteristics, enabling precise navigation decisions tailored to local lane conditions while maintaining overall system efficiency.
2Productivity
If lane-level traffic data is generated using sensor data from multiple vehicles, then navigation accuracy and traffic management efficiency improve, but the complexity of data collection and processing increases
Solution Approach 1:
The patent implements multi-functionality by designing a traffic data generation system that simultaneously serves multiple purposes: providing navigation instructions to drivers, enabling autonomous vehicle decision-making, supporting traffic management operations, and updating map databases. This universal system handles diverse data types (sensor data, probe data, map data) and produces multiple outputs, improving overall productivity while managing complexity through integrated architecture.
Solution Approach 2:
The patent incorporates feedback mechanisms where traffic data generated from sensor inputs is continuously updated and fed back into the navigation system. Real-time traffic conditions, vehicle speeds, and density measurements are processed and returned as actionable navigation instructions, creating a closed-loop system that improves efficiency through continuous optimization while managing complexity through iterative processing.
3Ease of operation
If traffic data is aggregated at road level only, then data processing remains simple, but the ability to provide accurate lane-specific navigation instructions deteriorates
Solution Approach 1:
The patent adds the lane dimension to traditional road-level traffic data processing. By introducing lane-level granularity as an additional dimension, the system transforms aggregated road data into detailed lane-specific information without completely abandoning the simplicity of road-level aggregation. This dimensional expansion preserves essential traffic patterns while capturing lane-level variations for accurate navigation instructions.
Solution Approach 2:
The patent performs preliminary aggregation of traffic data at road and link levels before proceeding to lane-level analysis. This preliminary action simplifies the overall processing by pre-processing and filtering data at higher levels, reducing the complexity of subsequent lane-level detailed analysis while preventing information loss through hierarchical data preparation.
Data Source
AI summary
A system and a method for determining lane-level traffic data is provided. The system is configured to obtain sensor data of each of a plurality of vehicles associated with a lane segment. The sensor data comprises at least one of: forward distance data of one or more vehicles in vicinity of each of the plurality of vehicles in the lane segment, or backward distance data of the one or more vehicles in the vicinity of each of the plurality of vehicles in the lane segment. The system is configured to determine lane distance data for the lane segment based on the sensor data, wherein the lane distance data comprises forward average distance data, or backward average distance data. The system is configured to determine traffic data for the lane segment based on the lane distance data.