Accident Image Selection Using Speed Profile Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current blackbox systems face challenges in efficiently distinguishing between actual and fake vehicle accidents, leading to unnecessary data transmission and storage issues, as they are designed to preserve all impact images due to low impact detection sensitivity, which results in increased costs and reduced storage capacity.
Innovation Solution
A method utilizing speed profile analysis before and after an impact event to determine the accident possibility by comparing the deceleration ratio with predetermined accident and safe deceleration ratios, allowing for the deletion or reclassification of images with low accident possibility and efficient management of actual accident images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impact detection sensitivity is set to a low level to detect all possible accidents, then actual accident detection accuracy is improved, but the quantity of stored images increases significantly including many fake accidents
Solution Approach 1:
The system performs preliminary speed profile analysis and deceleration ratio calculation immediately after impact detection, before permanently storing the image. By evaluating the deceleration ratio against predetermined thresholds, the system pre-filters images that are unlikely to be actual accidents, preventing unnecessary storage and transmission of fake accident images while maintaining high sensitivity for detecting actual accidents
Solution Approach 2:
The system changes the parameter of image storage status based on the calculated deceleration ratio. Images are classified into different categories (permanent storage, temporary storage, or deletion) according to whether their deceleration ratio falls within the accident deceleration ratio range. This parameter-based classification resolves the contradiction by dynamically adjusting storage behavior based on analytical results
2Reliability
If all impact images are permanently preserved, then no actual accident is missed, but storage medium capacity is quickly exhausted and lifespan is reduced
Solution Approach 1:
The system changes the storage status parameter of images based on deceleration ratio analysis. Images with deceleration ratios within the accident range are marked for permanent preservation, while images outside this range are marked for temporary storage or deletion. This dynamic parameter adjustment maintains reliability for actual accidents while extending storage medium lifespan by reducing unnecessary write operations
Solution Approach 2:
The system discards images that are determined to be fake accidents based on deceleration ratio analysis, and recovers storage space for actual accident images. By selectively deleting or overwriting images with low accident probability, the system preserves storage capacity and extends medium lifespan while maintaining high reliability for capturing actual accidents
3Measurement precision
If impact detection sensitivity is set low to capture minor collisions, then detection coverage is improved, but unnecessary data transmission and management costs increase
Solution Approach 1:
The system performs preliminary speed profile analysis and deceleration ratio calculation before transmitting images to cloud servers or management systems. By pre-evaluating the accident likelihood based on deceleration patterns, the system filters out fake accidents and transmits only images with high accident probability, significantly reducing data transmission volume and associated management costs while maintaining comprehensive detection coverage
Solution Approach 2:
The system uses feedback from speed sensor data and deceleration ratio calculations to determine transmission decisions. The feedback mechanism analyzes the deceleration profile and provides a classification result that directly controls whether an image should be transmitted, managed, or deleted, optimizing energy consumption and management costs based on actual accident likelihood
4Measurement precision
If impact detection sensitivity is set low to ensure comprehensive accident detection, then detection accuracy is improved, but time and economy are lost in identifying fake accidents
Solution Approach 1:
The system performs preliminary speed profile analysis and deceleration ratio calculation immediately after impact detection, before any manual review or transmission processes. This preliminary filtering action quickly identifies fake accidents based on unrealistic deceleration patterns, eliminating the need for time-consuming manual identification and reducing economic losses associated with processing fake accident reports
Data Source
AI summary
The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwritable state or taking measures for preventing the transmission of the image to a cloud server.