Blind-Spot Warning Sequencing for Faster Multi-Target Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional rear lateral blind-spot warning systems for vehicles face increased computational time and complexity due to the increased number of targets sensed by radar sensors, leading to slower determination of whether obstacles in the rear lateral blind spot satisfy warning conditions.
Innovation Solution
A rear lateral blind-spot warning system that employs a detection sensor, a sequence setter, and a warning determiner to efficiently determine if obstacles in the rear blind spot satisfy predetermined conditions by setting a sequence based on the sensing range and calculating satisfaction levels, allowing for sequential determination and reducing unnecessary computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the center frequency of the radar sensor is changed to improve sensing performance, then the number of targets that can be sensed increases, but the amount of computation increases, resulting in increased determination time
Solution Approach 1:
The determination process is divided into multiple sequences with different priorities. Critical determination items are processed first in a first sequence, while less critical items are processed in a second sequence. This segmentation allows the system to quickly complete essential determinations even when many targets are sensed, thereby reducing overall determination time while maintaining sensing performance.
2Area of stationary object
If the number of targets sensed by the radar sensor increases, then sensing coverage improves, but the computational load increases, slowing down the determination process
Solution Approach 1:
The determination items are segmented into multiple sequences based on their importance and computational requirements. The first sequence contains critical determination items that must be completed quickly, while the second sequence contains less critical items that can be processed afterward. This segmentation reduces the computational load on any single processing stage, enabling the system to handle a larger number of sensed targets without excessive delay.
Solution Approach 2:
Critical determination items are extracted and placed in a separate first sequence that is processed independently and prioritized. This extraction allows the system to focus computational resources on the most important determinations first, reducing the overall computational burden and enabling faster response times even when many targets are present.
3Reliability
If all predetermined conditions are checked for every sensed target, then determination accuracy is maintained, but processing speed decreases due to unnecessary computations
Solution Approach 1:
The determination process is segmented into sequences where critical conditions are evaluated first. If a target fails to meet critical conditions in the first sequence, further determination in the second sequence is skipped. This segmentation maintains determination accuracy for critical cases while improving processing speed by avoiding unnecessary computations for targets that clearly do not meet basic criteria.
Solution Approach 2:
The system performs partial determination by evaluating only the most critical conditions first. For targets that fail these critical checks, the system does not perform the full set of determinations, accepting that these targets are unlikely to be relevant. This partial action approach maintains sufficient accuracy for safety-critical applications while significantly improving processing throughput.
Data Source
AI summary
A rear lateral blind-spot warning system includes a detection sensor installed in a vehicle to sense an obstacle located in a rear blind spot or a lateral blind spot of the vehicle, a sequence setter configured to set the sequence, among multiple predetermined conditions, of determining, based on a sensing range of the detection sensor and the multiple predetermined conditions, whether the conditions are satisfied, and a warning determiner configured to sequentially determine, based on the sequence set by the sequence setter, whether the obstacle sensed by the detection sensor satisfies the multiple predetermined conditions and to determine, based on the result of the determination with regard to satisfaction of the conditions, whether the sensed obstacle is a target to be monitored.