Vehicle Sensor Detection Range Estimation Using Operational Data
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Solution Overview
Problem
Conventional methods for determining the detection range of sensors on motor vehicles, such as LIDAR, RADAR, and cameras, face challenges in changing weather conditions and dense traffic, relying on map data or labeled training data, which are unreliable and require extensive data collection, limiting their ability to accurately determine the field of view based solely on operational data.
Innovation Solution
A method that uses a camera to detect objects, determine their distance, and calculate the detection range by filtering out irrelevant detections, using repeated object sightings to confirm valid detections, and applying weighted filters to combine current and previous detection range data, allowing for self-movement compensation and object classification-based range determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map-based approach is used to determine detection range, then detection range can be estimated using predetermined objects, but the system fails in dense traffic when real objects obscure map objects and requires sufficient infrastructure elements
Solution Approach 1:
The sensor system determines its own detection range using only its acquired operational data, without relying on external map data or predetermined objects. The control device analyzes detection results from the sensor itself to calculate the detection range, making the system self-sufficient and adaptable to any environment including dense traffic and sparse infrastructure scenarios
Solution Approach 2:
The invention introduces an intermediary statistical analysis layer that processes sensor detection results over time. By evaluating detection consistency and using statistical methods on operational data, the system mediates between raw sensor data and detection range determination, enabling reliable estimation without external references
2Measurement precision
If data-driven approach with labeled training data is used, then field of view can be estimated, but large amounts of labeled training data are required which are difficult to obtain and label
Solution Approach 1:
The system uses its own operational detection data to determine detection range without requiring external labeled training data. By continuously analyzing its detection results and using statistical evaluation of detection consistency, the sensor system self-calibrates and determines its field of view using only the data it collects during normal operation
Solution Approach 2:
The invention changes the approach from using fixed labeled training data to dynamically analyzing detection parameters from operational data. By evaluating detection consistency, object frequency, and statistical patterns in real-time data, the system adapts to varying conditions and determines detection range without requiring large labeled datasets
3Ease of operation
If conventional sensors rely solely on acquired data, then they can operate independently, but they cannot reliably detect or determine detection range when sensor performance varies in changing weather conditions
Solution Approach 1:
The control device continuously monitors sensor detection results and uses this feedback to dynamically determine detection range. By analyzing detection consistency over time and comparing detection results with statistical patterns, the system adapts to changing weather conditions and maintains reliable detection range determination while operating independently
Solution Approach 2:
The invention makes the detection range determination dynamic rather than static. The system continuously updates detection range based on current operational data and detection consistency, allowing it to adapt to varying sensor performance in different weather conditions while maintaining independent operation
Data Source
AI summary
A method for determining a detection range of a sensor installed in a motor vehicle is provided. The sensor scans a surroundings of the motor vehicle. The method includes detecting a predefined object in the surroundings of the motor vehicle by way of the sensor, determining a distance of the detected object to the motor vehicle and determining the detection range based on the determined distance.