Vehicle Motion State Determination Using Route-Constrained Error Separation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional motion state determination technologies are prone to errors due to observation errors, especially when the target object is far from the sensor, leading to incorrect classification of meandering or non-meandering states.
Innovation Solution
A motion state determination apparatus that includes a sensor unit, route data storage, route component prediction, coordinate transformation units, and a state determination unit, which calculates and transforms motion dimension prediction values and errors into specific coordinate systems to accurately determine the motion state of a target object, reducing erroneous determinations caused by observation errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion state determination is performed based on observation data, then the motion state can be determined, but determination errors increase when the target object is far from the sensor due to larger observation errors
Solution Approach 1:
The patent introduces route data as an intermediary element that mediates between the sensor observation data and the motion state determination. By comparing observed position changes against expected route geometry, the system can distinguish between genuine meandering motion and position errors caused by observation inaccuracies, especially when the target is far from the sensor.
Solution Approach 2:
The patent changes the determination parameter from raw position data to a derived parameter that combines position data with route information. By transforming the determination basis from direct position comparison to route-constrained position analysis, the system improves measurement precision while maintaining reliability across varying distances.
2Measurement precision
If the threshold for determining meandering is set to be strict, then fine meandering can be detected, but observation errors are more likely to be misclassified as meandering
Solution Approach 1:
The patent applies different determination criteria locally based on the target object's distance from the sensor. For distant targets where observation errors are larger, the system uses more conservative thresholds and greater emphasis on route consistency. For nearby targets with smaller observation errors, the system can use stricter thresholds to detect finer meandering, thus achieving local optimization of both sensitivity and reliability.
Solution Approach 2:
The patent makes the determination threshold dynamic rather than fixed. The threshold adapts based on the target distance and associated observation error magnitude. This dynamic adjustment allows the system to maintain high meandering detection sensitivity for nearby targets while reducing false positives for distant targets, resolving the contradiction between detection sensitivity and false positive rate.
Data Source
AI summary
A motion state determination apparatus according to the present disclosure includes a sensor for obtaining observation data on a target object, a route data storage unit, a route component predictor that calculates component parallel and vertical to the route of a motion-dimension prediction value and a prediction error, a first coordinate transformer that transforms a motion-dimension prediction value and a prediction error into those on a coordinate system the same as a first coordinate system, a filter that calculates a motion-dimension estimation value and an estimation error, a second coordinate transformer that transforms a motion-dimension estimation value and an estimation error into a component parallel to the route and a component vertical to the route and a motion-dimension prediction value and a prediction error, and a state determinator that determines a motion state of the target object. As a result, the frequency of an erroneous determination can be decreased.