Rear Cross-Traffic Warning Control Using Intrusion Probability
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Solution Overview
Problem
Radar sensors in vehicles often generate unnecessary warning alerts and collision prevention controls when there is no actual risk of collision with target vehicles during reversing, causing driver discomfort.
Innovation Solution
A rear warning system that utilizes a combination of sensors, including rear side radar, ultrasonic sensors, and surround view monitors, to collect road information and determine the probability of a target vehicle intruding into the vehicle's expected driving lane, thereby controlling the rear cross-traffic collision prevention function to deactivate unnecessary warnings and controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar sensors are used to detect target vehicles in the rear during reversing, then collision detection capability is improved, but false warnings and unnecessary collision prevention controls are generated
Solution Approach 1:
The patent combines multiple sensor types (radar sensors, cameras, ultrasonic sensors) to detect target vehicles during reversing. By merging the detection capabilities of different sensors, the system cross-validates detections to distinguish real collision risks from false alarms, thereby maintaining high reliability while reducing unnecessary warnings
Solution Approach 2:
The system continuously monitors detected target vehicles using multiple sensors and provides feedback to adjust warning behavior. When multiple sensors confirm a target vehicle's presence and potential intrusion path, warnings are activated; when sensors indicate no real risk, warnings are suppressed, creating a feedback loop that reduces false alarms while maintaining safety
2Speed
If the rear cross-traffic collision prevention function is activated based on radar detection, then safety response time is improved, but driver discomfort increases due to unnecessary alerts
Solution Approach 1:
The system dynamically adjusts the activation state of collision prevention controls based on real-time sensor data. When multiple sensors detect a genuine collision risk, the system quickly activates controls; when sensors indicate no real threat, controls remain inactive. This dynamic response maintains fast safety reaction times while avoiding driver discomfort from unnecessary alerts
Solution Approach 2:
The system changes detection parameters and warning thresholds based on sensor fusion results. When multiple sensors confirm a target vehicle, the system lowers warning thresholds and activates controls faster; when sensor data suggests no real risk, thresholds are raised or controls are suppressed, optimizing both response time and driver comfort based on actual conditions
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
Reduces driver discomfort by preventing false alarms and improving the reliability of collision prevention systems by ensuring warnings and controls are only activated when a collision risk is present.
Implementation Method 1
Radar sensors detect target vehicles and objects within the sensor's detection range (FOV: Field of View) using radio waves
Implementation Method 2
The at least one sensor may include one or more of a rear side radar, a rear ultrasonic sensor
Data Source
AI summary
A rear warning system for a vehicle and a control method thereof are introduced, and the control method includes activating a rear cross-traffic collision prevention function, collecting, upon the activation of the rear cross-traffic collision prevention function being activated, road information between the vehicle and a target vehicle present in a rear or rear side of the vehicle using at least one of sensors installed in the vehicle, and controlling the rear cross-traffic collision prevention function based on a probability of intrusion of the target vehicle into an expected driving lane of the vehicle when the vehicle is reversing, the probability of intrusion being determined based on the collected road information.