Blindzone Object Detection via Multi-Modal Sensor Fusion
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Solution Overview
Problem
Operators of vehicles face challenges in detecting objects within the blindzone, an area that cannot be seen by rear or side view mirrors, especially when maneuvering or changing lanes, which increases the risk of collisions.
Innovation Solution
A system comprising a sensor array, a blindzone object detector with frequency-based, time-based, and image-based detectors, and an alarm system that processes measurement data to generate a final detection value and alerts the operator of potential objects in the blindzone, using environmental data to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple detectors (frequency-based, time-based, image-based) are used to improve detection accuracy in the blindzone, then the reliability of object detection is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple different types of detectors (frequency-based, time-based, and image-based detectors) into a single integrated blindzone object detection system. These detectors work together to process measurement data from the sensor array, with each detector type contributing different detection capabilities. The outputs from all detectors are combined to form a final detection value, thereby improving overall detection reliability while managing system complexity through unified architecture.
Solution Approach 2:
The blindzone object detection system is designed to perform multiple detection functions simultaneously using a single integrated system. The frequency-based detector analyzes frequency characteristics, the time-based detector processes temporal information, and the image-based detector processes visual data. This multi-functional approach allows the system to detect objects under various conditions and with different detection methods, improving reliability without requiring separate independent systems.
2Measurement precision
If environmental data is used to augment detector parameters and improve detection accuracy, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system incorporates environmental data (such as temperature, humidity, light conditions) that provides feedback about the operating conditions to the blindzone object detector. This environmental information is used to dynamically adjust and augment the parameters of the detectors, allowing them to optimize their detection algorithms based on current environmental conditions. This feedback mechanism improves measurement precision by adapting detection sensitivity and thresholds to match environmental context.
Data Source
AI summary
Various embodiments are described herein for a system and method for blindzone obstacle detection for a host vehicle. The system comprises a sensor array configured to generate measurement data for a blindzone of the host vehicle; a blindzone object detector having at least two detectors that are coupled to the sensor array to process the measurement data and generate outputs which are then combined to form a final detection value that is used to detect an object in the blindzone of the host vehicle. An indicator can also be coupled to the blindzone object detector to generate an indication of object detection in the blindzone.