V2X GNSS Quality Filter for Positioning Accuracy
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Solution Overview
Problem
Current V2X technologies rely on GNSS positioning solutions that can be deteriorated by noise and bias from sources like time delay, atmospheric effects, and multipath errors, leading to inaccurate vehicle-to-pedestrian safety systems.
Innovation Solution
A novel quality filter system that evaluates up to four metrics (speed, heading angle change, curvature, and lateral displacement) from GNSS and onboard vehicle sensors to assess the validity of GNSS signals, ensuring accurate positioning for V2X applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GNSS positioning solution is used for V2X applications, then positioning capability is provided, but positioning accuracy deteriorates due to noise and bias from error sources
Solution Approach 1:
The patent introduces an intermediary quality filter system that mediates between the GNSS positioning solution and V2X applications. This filter evaluates multiple metrics (speed, heading angle change, curvature, lateral displacement) to assess GNSS signal quality and determine whether positioning data should be trusted, thereby protecting V2X applications from inaccurate positioning without eliminating the GNSS capability itself
Solution Approach 2:
The system implements feedback by continuously monitoring multiple kinematic variables and comparing them against expected physical constraints. The quality filter uses feedback from speed, heading angle change, curvature, and lateral displacement measurements to dynamically assess GNSS signal quality and provide feedback on whether the positioning solution is reliable for V2X applications
2Measurement precision
If multiple metrics are evaluated to assess GNSS signal quality, then positioning accuracy improves, but system complexity increases
Solution Approach 1:
The quality filter system is segmented into distinct evaluation modules, each responsible for assessing a specific metric (speed evaluation, heading angle change evaluation, curvature evaluation, lateral displacement evaluation). This segmentation allows the complex assessment task to be divided into manageable, independent components that can be processed sequentially
Solution Approach 2:
The quality filter system serves multiple functions: it evaluates speed consistency, heading angle change合理性, curvature constraints, and lateral displacement limits. By designing a universal filter that performs all these evaluations through a common framework, the system avoids the need for separate specialized filters for each metric, thereby managing complexity
Data Source
AI summary
This provides methods and systems for V2X applications, such as forward collision warning, electronic emergency brake light, left turn assist, work zone warning, signal phase timing, and others, mainly relying on a GNSS positioning solution transmitted via the Dedicated Short-Range Communications (DSRC) to/from the roadside units and onboard units in other V2X-enabled vehicles. However, the positioning solution from a GNSS may be deteriorated by noise and/or bias due to various error sources, e.g., time delay, atmospheric effect, ephemeris effect, and multipath effect. This offers a novel quality filter that can detect noise and the onset of drift in GNSS signals by evaluating up to four metrics that compare the qualities of kinematic variables, speed, heading angle change, curvature, and lateral displacement, obtained directly or derived from GNSS and onboard vehicle sensors. This is used for autonomous cars and vehicle safety, with various examples/variations.