Roadside Object Detection Using Adaptive Height Thresholds
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Solution Overview
Problem
The road model used in roadside object detection systems can decrease in accuracy, leading to failures in accurate detection of roadside objects.
Innovation Solution
A height-related threshold is determined based on the positional relationship between the host vehicle and roadside object candidates to identify potential roadside objects, adjusting the detection criteria according to distance and vehicle conditions such as speed and acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed road model is used for roadside object detection, then the detection process is simple and fast, but the detection accuracy decreases when road conditions vary
Solution Approach 1:
The patent applies dynamics by making the detection threshold adaptive rather than fixed. The height-related threshold is dynamically adjusted based on the positional relationship between the host vehicle and roadside object candidates, allowing the system to adapt to varying road conditions and maintain high detection accuracy without requiring an overly complex system
Solution Approach 2:
The patent changes the parameter of the detection threshold based on positional relationships. By varying the height-related threshold according to distance and vehicle conditions (speed and acceleration), the system optimizes detection accuracy for different scenarios without fundamentally changing the detection architecture
2Reliability
If the detection threshold is lowered to detect more objects, then false negatives decrease, but false positives increase
Solution Approach 1:
The patent applies local quality by setting different detection thresholds for different spatial locations and vehicle conditions. Instead of using a uniform threshold, the system adjusts the height-related threshold based on the specific positional relationship between the vehicle and detected candidates, ensuring optimal detection accuracy for each local context while maintaining overall reliability
3Measurement precision
If the detection threshold is raised to reduce false positives, then detection precision improves, but false negatives increase
Solution Approach 1:
The system dynamically adjusts the detection threshold based on vehicle conditions such as speed and acceleration. When the vehicle is stationary or moving slowly, a higher threshold can be used to reduce false positives. When the vehicle is moving quickly, the threshold is adjusted to prevent false negatives, thus maintaining both precision and reliability across different operating conditions
Data Source
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AI summary
The roadside object detection device, roadside object detection method, and roadside object detection system according to the present invention make it possible to accurately detect roadside objects by: determining a first feature value regarding positional relationship between a host vehicle and a roadside object candidate and a second feature value regarding a height of the roadside object candidate, based on external environment information acquired by an external environment recognition unit; determining a height-related threshold for identifying the roadside object candidate as a roadside object, based on the first feature value; and identifying the roadside object candidate as a roadside object when the second feature value exceeds the threshold.