Object Detection Probability Modeling for Degraded Vehicle Monitoring Images
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Solution Overview
Problem
In automated driving systems, monitoring images transmitted from vehicles to a monitoring center can deteriorate due to wireless band fluctuations, leading to reduced object detection probability by operators, which may result in accidents due to undetected hazards.
Innovation Solution
An object detection probability calculating apparatus that calculates the probability of an operator detecting an object based on image quality parameters and distance information, using a model that correlates bit rate and distance to determine the likelihood of object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If monitoring images are transmitted from vehicles to monitoring center via wireless communication, then real-time monitoring capability is improved, but image quality deteriorates due to band fluctuation
Solution Approach 1:
The system calculates object detection probability in advance based on image quality parameters (bit rate, resolution, frame rate) and distance information before actual object detection occurs. This preliminary calculation allows the system to predict detection capabilities under various transmission conditions, enabling proactive adjustments to monitoring strategies rather than reactive responses after image degradation occurs.
Solution Approach 2:
The system continuously monitors image quality parameters during transmission and uses this feedback to dynamically adjust monitoring operations. By measuring actual bit rate, resolution, and frame rate achieved during wireless transmission, the system can recalculate object detection probability and adapt monitoring intensity, alert thresholds, and resource allocation in real-time to compensate for transmission-induced quality degradation.
2Productivity
If image quality parameter thresholds are set low to maintain more connections, then system availability is improved, but object detection accuracy deteriorates
Solution Approach 1:
The system dynamically adjusts operational parameters based on calculated object detection probability. When probability falls below thresholds due to poor image quality, the system changes parameters such as alert thresholds, monitoring intensity, and resource allocation rather than simply accepting or rejecting connections. This allows the system to maintain availability while compensating for reduced detection accuracy through adaptive parameter modification.
3Area of stationary object
If multiple vehicles are monitored simultaneously with divided screens, then monitoring coverage is improved, but operator awareness of image quality deterioration is reduced
Solution Approach 1:
The system introduces an automated intermediary mechanism that calculates and communicates image quality status to operators. Rather than relying on operator visual inspection of multiple divided screens, the system automatically measures image quality parameters, calculates detection probability, and presents this information through automated alerts and notifications. This intermediary automation resolves the contradiction by providing comprehensive monitoring coverage while maintaining operator awareness through systematic quality reporting.
Data Source
AI summary
An object detection probability calculating apparatus includes a processor; and a memory storing instructions that cause the processor to execute a process. The process includes calculating an object detection probability indicating a probability at which a person is able to detect a predetermined object appearing in an image, based on a parameter of image quality acquired from a camera provided at a moving body capable of automatic movement and distance information indicating a distance from the moving body or the camera to the predetermined object.