Relative Position Estimation for Mobile Objects Using Reference Identification
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Solution Overview
Problem
Existing relative position estimation methods for mobile objects, such as vehicles, face inaccuracies when the preceding vehicle is outside the detection range of ranging sensors or when determining the rearward area based on road angles and swing angles, leading to potential errors in collision risk assessment.
Innovation Solution
A position estimation apparatus that acquires position histories of both target and nearby mobile objects, identifies reference positions based on their movement states, and estimates the relative position between them using these identified references.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS positioning is used to acquire vehicle position information, then position information can be obtained, but position accuracy deteriorates due to ionospheric delays, multipath effects, and system delays
Solution Approach 1:
The patent introduces a mediator approach by using relative position estimation based on inter-vehicle distance measurements (e.g., from radar or communication signals) as an intermediary to bypass the inaccurate absolute GPS positioning. Instead of relying directly on GPS coordinates, the system estimates relative positions by measuring distances between vehicles and combining them with map data, thereby eliminating the direct impact of ionospheric delays, multipath effects, and system delays on position accuracy.
2Adaptability or versatility
If relative position estimation methods are switched based on road geometry (straight or curved), then position estimation can be adapted to road conditions, but accuracy deteriorates when the preceding vehicle is outside the detection range of ranging sensors
Solution Approach 1:
The patent applies universality by creating a unified position estimation framework that works across all scenarios - whether the preceding vehicle is within or outside the detection range of ranging sensors. The system uses map data and inter-vehicle distance information as universal inputs that remain valid regardless of sensor detection capabilities. This multi-functional approach allows the system to maintain position estimation accuracy in both situations by switching between different calculation modes while using the same fundamental data sources.
3Adaptability or versatility
If the rearward area is rotated based on road crossing angle and vehicle swing angle, then the detection area can be adjusted to vehicle orientation, but accuracy deteriorates due to errors in swing angle determination
Solution Approach 1:
The patent extracts the problematic swing angle determination from the position estimation process. Instead of relying on inaccurate swing angle measurements to rotate the rearward area, the system separates the orientation adjustment from the core position calculation. By using map data and relative distance measurements as the primary basis for position estimation, the system removes the harmful influence of swing angle errors while still maintaining adaptability to vehicle orientation through selective use of orientation data only when reliable.
Data Source
AI summary
A reference identification unit identifies a target reference position to be a reference from a position history indicated in target information, based on a movement state of a target object, and identifies a nearby reference position to be a reference from a position history indicated in nearby information, based on a movement state, estimated from the nearby information, of a nearby object which is a mobile object present in the vicinity of the target object. A position estimation unit estimates a relative position between the target object and the nearby object, based on the target reference position and the nearby reference position.


