Vehicle Perception Maneuvering With Multi-Level Sensor Confidence
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Solution Overview
Problem
Autonomous vehicles face challenges in safely maneuvering on high-speed roadways due to delayed detection of objects, particularly when occlusions or noise in sensor data hinder timely recognition of potential collisions, leading to potential safety risks during merging or turning.
Innovation Solution
Implementing a multi-level sensor range system with a less precise outer sensor range and a more precise inner range, allowing for earlier detection and response based on confidence levels, where preliminary actions can be taken upon detection in the outer range and verified in the inner range, using various sensors like radar, LIDAR, and cameras, and cross-validation techniques to improve confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle waits for high-confidence detection in the inner sensor range before taking action, then false positives are reduced, but response time is delayed and safety is compromised
Solution Approach 1:
The system performs preliminary actions based on low-confidence detections from the outer sensor range before high-confidence confirmation is available. When an object is detected in the outer range, the vehicle proactively adjusts its state (e.g., prepares to brake, selects alternative routes) in advance, rather than waiting for certain detection. This preliminary action resolves the contradiction by accepting some risk of false positives in exchange for significantly reduced response time.
Solution Approach 2:
The system cushions against potential false positives by maintaining multiple ready-to-execute actions with varying confidence levels. Low-confidence detections trigger preparatory actions that can be quickly adjusted or canceled if proven false, while high-confidence detections trigger definitive actions. This layered approach allows the system to respond immediately to potential hazards while having built-in protection against erroneous detections.
2Loss of time
If the vehicle takes immediate action based on noisy detections in the outer sensor range, then response time is improved, but false positives increase and reliability decreases
Solution Approach 1:
The system applies different quality standards to different sensor ranges. The outer sensor range accepts lower-quality, noisier detections with lower confidence thresholds to enable early warning, while the inner sensor range requires higher-quality detections with higher confidence thresholds for confirmation. This spatial differentiation of detection quality allows the system to respond quickly to potential hazards while maintaining high reliability for final action execution.
Solution Approach 2:
The confidence threshold for triggering actions is dynamic rather than fixed. The system adjusts the threshold based on the sensor range, environmental conditions, and current vehicle state. In the outer range, lower thresholds enable early detection, while in the inner range, higher thresholds ensure accuracy. This dynamic adjustment resolves the contradiction by adapting the reliability requirement to the specific detection context.
3Measurement precision
If the vehicle uses a single high-precision sensor range for detection, then detection accuracy is improved, but early warning capability is lost
Solution Approach 1:
The sensor detection space is segmented into multiple ranges with different precision requirements. The outer range captures distant objects with lower precision to provide early warning, while the inner range provides high-precision confirmation. This segmentation allows the system to benefit from both early detection and accurate measurement, resolving the contradiction between early warning capability and detection precision.
Solution Approach 2:
The system adds a spatial dimension to the detection strategy by creating concentric sensor ranges at different distances. Rather than using a single detection threshold, the system uses distance as an additional dimension to determine detection confidence and trigger appropriate responses. This dimensional approach enables early warning from distant detections while maintaining precision for close-range confirmation.
Data Source
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AI summary
A system and method is provided for early detection of objects by a perception system of a vehicle, and triggering a precautionary action by the vehicle in response without waiting for a more precise detection. The vehicle has a multi-level sensor range, wherein a first level of the sensor range is adjacent an outer bounds of the sensor range and has a first confidence value, and a second level of the sensor range is within the first range and has a second higher confidence value. In situations when oncoming traffic is traveling at a high rate of speed, the vehicle responds to noisier detections, or objects perceived with a lower degree of confidence, rather than waiting for verification which may come too late.