Vehicle Collision Warning Using Radar-Vision Time-to-Collision Fusion
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Solution Overview
Problem
Existing vehicle collision warning systems fail to accurately recognize obstacle categories and provide timely warnings, leading to ineffective collision avoidance.
Innovation Solution
Integrate millimeter-wave radar with monocular vision to determine motion parameters of obstacles and vehicles, using a deep neural network for obstacle recognition and fusion of radar and image information to calculate collision time for timely warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a warning system continuously detects road conditions to help users avoid traffic accidents, then the safety warning function is improved, but the obstacle recognition accuracy deteriorates
Solution Approach 1:
The patent combines millimeter-wave radar detection with monocular vision recognition into an integrated warning system. The radar provides continuous detection data while the vision system provides obstacle classification, merging both technologies to simultaneously improve safety warning reliability and obstacle recognition accuracy rather than having to choose one or the other
2Reliability
If the warning system continuously detects road conditions, then the warning coverage is improved, but the warning timing accuracy deteriorates
Solution Approach 1:
The system uses real-time feedback from both radar and vision systems to continuously update obstacle position, speed, and trajectory. This feedback mechanism allows the system to maintain accurate warning timing by dynamically adjusting predictions based on current motion parameters while keeping continuous warning coverage
3Measurement precision
If millimeter-wave radar and monocular vision are integrated to determine motion parameters, then the obstacle recognition accuracy is improved, but the device complexity increases
Solution Approach 1:
The integrated system uses both radar and vision data for multiple functions: obstacle detection, classification, motion parameter estimation, and collision time prediction. By making the integrated system multi-functional, the patent justifies the increased complexity through substantial improvements in measurement precision and system capability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves obstacle recognition accuracy and warning timing, enhancing safe driving by providing precise collision alerts.
Implementation Method 1
determines the motion parameters of obstacles and vehicles according to radar information
Implementation Method 2
based on the method of integrating monocular vision with the millimeter-wave radar
Data Source
AI summary
A method for collision warning implemented in an electronic device includes fusing obtained radar information and image information; recognizing at least one obstacle in a traveling direction of a vehicle according to the fused radar information and image information; determining motion parameters of the at least one obstacle and the vehicle according to the radar information and the image information; and calculating a collision time between the vehicle and the at least one obstacle according to the motion parameters, and issuing a collision warning.