Vehicle Adjusting Part Obstacle Detection and Collision Data Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle adjustment systems do not effectively detect and store environmental conditions during obstacle detection, nor do they provide a means to assess warranty claims related to collisions with obstacles.
Innovation Solution
The proposed solution involves storing curves of control signals and measured values from the electronic detection device, along with curves from on-board sensors that change significantly during collisions, to enable subsequent plausibility checks and analysis of collision scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If curves of control signals and measured values are stored for subsequent analysis, then the ability to assess warranty claims and detect malfunctions is improved, but the data storage requirements and system complexity increase
Solution Approach 1:
The system performs preliminary actions by storing control signals and measured value curves during normal operation before any collision event occurs. This preparatory data collection enables subsequent plausibility checks and warranty assessments without requiring additional hardware or complex processing at the time of incident analysis.
Solution Approach 2:
Instead of storing raw sensor data continuously, the system creates simplified copies in the form of pre-evaluated plausibility indicators and characteristic curves. These copied representations capture the essential information needed for warranty assessment while occupying minimal storage space and requiring simple retrieval operations.
2Measurement precision
If multiple sensor curves are stored and correlated for plausibility checks, then the precision of collision detection and malfunction identification is improved, but the measurement and data processing complexity increases
Solution Approach 1:
The system merges multiple sensor curves (control signals, measured values, environmental conditions) into a single correlated dataset indexed by time stamps. This combination approach maintains the precision benefits of multi-sensor analysis while simplifying the detection process through unified data structure and automated temporal alignment.
Solution Approach 2:
The system employs feedback mechanisms by continuously comparing stored historical curves with real-time sensor data. This feedback loop automatically identifies deviations and plausibility issues without requiring complex manual analysis, thereby improving measurement precision while keeping the detection system relatively simple through automated anomaly recognition.
3Loss of information
If environmental conditions during obstacle detection are recorded, then the completeness of collision scenario analysis is improved, but the data storage volume and retrieval complexity increase
Solution Approach 1:
The system extracts only the essential environmental condition parameters relevant to collision analysis (temperature, humidity, lighting) from the complete sensor dataset. This extraction process preserves the necessary contextual information for comprehensive scenario analysis while eliminating redundant data, thereby reducing overall storage requirements and simplifying retrieval operations.
Data Source
AI summary
A method for adjusting an adjusting part of a vehicle including controlling by an electronic detection device configured to detect a potential obstacle in an adjustment path of the adjusting part based on at least one first measured value and generates at least one control signal. The method including storing and correlating, over a defined time period, at least one of a curve of the control signal the first measured value, and a curve of at least one second measured value changing significantly in response to a collision of the adjusting part and an obstacle for a subsequent plausibility check.