Dynamic Threshold Position Estimation for Mobile Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle position estimation systems face challenges in accurately determining vehicle position due to varying conditions such as terrain, temperature, and driver characteristics, leading to increased modeling errors when using fixed threshold values for switching between mathematical expression models.
Innovation Solution
A position estimation device that calculates a dynamic threshold value based on real-time error calculations and condition quantities, allowing for the selection of the most appropriate mathematical expression model for accurate vehicle position estimation, using a probability model filtering processing unit, threshold calculation unit, and threshold value determining unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed threshold value is used for switching between mathematical expression models, then the device complexity is reduced and ease of operation is improved, but the measurement precision and reliability of vehicle position estimation deteriorate under varying conditions
Solution Approach 1:
The patent implements dynamic threshold values that automatically adjust based on current vehicle operating conditions. The threshold calculation unit computes thresholds in real-time using probability models that consider terrain, temperature, and other environmental factors, replacing fixed thresholds with adaptive, condition-dependent thresholds to maintain positioning accuracy across varying conditions
Solution Approach 2:
The system incorporates feedback mechanisms where the threshold calculation unit continuously monitors positioning errors and condition quantities, then adjusts thresholds accordingly. The error information from position estimation is fed back into the threshold calculation process, creating a closed-loop system that optimizes threshold values based on actual performance and environmental conditions
2Reliability
If a fixed threshold value is set in advance, then the ease of operation is improved, but the reliability of position estimation deteriorates due to increased modeling error under varying conditions
Solution Approach 1:
The system performs self-adjustment through automated threshold calculation. The threshold calculation unit independently computes appropriate threshold values based on current condition quantities and probability models without requiring manual intervention or configuration, enabling the system to adapt to varying conditions while maintaining reliability
Solution Approach 2:
The patent changes the parameter values of thresholds dynamically based on operating conditions. Instead of using fixed parameter values, the system adjusts threshold parameters in real-time according to terrain, temperature, and other environmental factors, allowing the position estimation reliability to be maintained across diverse conditions
3Adaptability or versatility
If multiple mathematical expression models are prepared with switching based on fixed thresholds, then the adaptability to different conditions is improved, but the measurement precision deteriorates due to fixed threshold limitations
Solution Approach 1:
The system dynamically selects mathematical expression models based on real-time threshold calculations rather than fixed thresholds. The threshold calculation unit computes condition-specific thresholds that enable accurate model selection across varying environmental conditions, improving both adaptability and precision simultaneously
Solution Approach 2:
The system prepares multiple mathematical expression models in advance for different operating conditions. By pre-configuring multiple models and using dynamic threshold calculation to select the appropriate one, the system enables accurate position estimation across diverse conditions without requiring real-time model development
Data Source
AI summary
A position estimation device includes: a mathematical expression model processing unit that calculates a position of a mobile object, a condition quantity indicating a moving condition of the mobile object and an error in the condition quantity through filtering processing executed by using a probability model based upon an attitude information and a positioning information of the mobile object having been obtained from sensors and a specific mathematical expression model among a plurality of mathematical expression models expressing behavior of the mobile object; a threshold calculation unit that calculates a threshold candidate value for a threshold value to be used as a criterion when selecting the specific mathematical expression model, by using the error; a threshold value determining unit that determines the threshold value based upon the threshold candidate value; and a mathematical expression model selection unit that selects the specific mathematical expression model based upon the threshold value.