Cross-Traffic Alert Thresholds Adapted to Driving Environment
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Solution Overview
Problem
Conventional cross-path detection systems use static alert zones that fail to adapt to different driving environments, leading to inaccurate alerts due to inconsistent threshold requirements, such as false positives or negatives in parking lots and roadways.
Innovation Solution
A cross-traffic alert system that dynamically adjusts longitudinal alert thresholds based on classified driving environments, using radar and camera systems to detect and filter target objects, and adapt alert zones to scenarios like parking lots or roadways, ensuring accurate detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single static threshold is used for cross traffic alert, then the system is simple to implement, but the alert accuracy deteriorates in different driving environments
Solution Approach 1:
The patent implements dynamic threshold adjustment by transitioning from a single static threshold to multiple environment-specific thresholds (parking lot threshold, road threshold, intermediate threshold). The system dynamically selects and switches between these thresholds based on detected environmental conditions, allowing the alert zone to adapt its size and sensitivity to match the current driving context, thereby resolving the contradiction between system simplicity and alert accuracy.
Solution Approach 2:
The patent changes the threshold parameter based on environmental classification. By detecting environmental features (such as presence of curbs, road markings, or parking lot structures) and classifying the current environment type, the system adjusts the longitudinal threshold parameter to appropriate values: extended threshold for parking lots, reduced threshold for roads, and intermediate values for transition zones. This parameter adaptation resolves the contradiction by maintaining accuracy across different environments while keeping the underlying system architecture relatively simple.
2Reliability
If the alert threshold is extended to cover the width of a parking lane, then all incoming targets are detected in parking lots, but false positives increase on roadways
Solution Approach 1:
The patent applies local quality by implementing different threshold characteristics for different spatial environments. Instead of using a uniform threshold across all locations, the system creates environment-specific threshold configurations: a wider, more inclusive threshold for parking lot environments and a narrower, more selective threshold for roadway environments. This localized adaptation of threshold properties ensures high detection coverage where needed while minimizing false positives where not needed.
Solution Approach 2:
The patent makes the alert threshold dynamic by switching between different threshold configurations based on real-time environmental detection. The system continuously monitors environmental features and dynamically adjusts the threshold size and sensitivity accordingly. This dynamic behavior allows the threshold to expand for comprehensive coverage in parking lots while contracting to reduce false positives on roads, resolving the contradiction between detection coverage and false positive rate.
3Object-generated harmful factors
If the alert threshold is reduced to include only targets travelling on a first lane, then false positives are reduced on busy roads, but detection coverage is insufficient
Solution Approach 1:
The patent implements local quality by applying different threshold strictness levels to different environmental contexts. For roadway environments, the system uses a more restrictive threshold that focuses on lane-specific targets, reducing false positives from distant or irrelevant objects. For parking lot environments, it uses a more inclusive threshold that captures all potential targets within the parking lane area. This localized threshold quality resolves the contradiction by optimizing for false positive reduction where appropriate while maintaining detection coverage where needed.
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
The system provides adaptive alert zones that reduce false positives and negatives by accurately distinguishing between different driving environments, enhancing safety and reducing unnecessary alerts.
Implementation Method 1
a target detection sensor, such as a radar sensor
Data Source
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AI summary
Cross traffic alert system for a host vehicle engaged in a forward or reverse gear position, includes an object detection sensor configured to detect relative positons of a plurality of target objects present in a coverage zone proximate the vehicle, and a processor for receiving the target positional data, detecting established environmental states based on the received data, and classifying a driving environment (e.g., road, parking lot, etc.) based on the detection or not of established environmental states. Threshold alert areas are dynamically adjustable in the coverage zones based on the classified driving environment, where indications of targets in the alert areas may be generated.