Multi-Vehicle Sensor Diagnosis via V2V Comparison
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Solution Overview
Problem
Modern vehicles equipped with advanced driver-assistance systems (ADAS) face challenges in accurately diagnosing and calibrating perception sensors, especially as they age, due to environmental factors and the difficulty of comparing sensor data within the vehicle, which can lead to reduced accuracy and increased risk of incidents.
Innovation Solution
A system and method for diagnosing perception sensors by exchanging and comparing sensor information between vehicles using a V2V communication system, where a processor generates a sensor confidence score based on comparisons between host vehicle and remote vehicle data, enabling assisted driving operations and refining sensor confidence scores through aggregate measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors on the same vehicle are used for comparison, then sensor accuracy can be verified, but all sensors have aged equally and may have been subject to the same external conditions making comparison problematic
Solution Approach 1:
The patent uses a remote vehicle as an intermediary to provide independent sensor data for comparison. Instead of comparing sensors that have all been exposed to the same environmental conditions and aging, the system receives sensor data from a remote vehicle that has captured the same target object under different conditions, serving as a mediator to validate sensor accuracy.
Solution Approach 2:
The system obtains a copy of sensor data from a remote vehicle that has captured the same target object. This copied data from an independent source allows for comparison without the limitations of using only locally mounted sensors that share the same environmental exposure and aging characteristics.
2Measurement precision
If a vehicle is brought into a repair facility for sensor calibration, then sensor accuracy can be restored, but it is inconvenient for the vehicle operator and may be delayed
Solution Approach 1:
The system enables self-service sensor diagnosis and calibration by using automated comparison of sensor data with remote vehicle data. The vehicle can perform its own sensor validation and identify calibration needs without requiring operator intervention to visit a repair facility, making the process convenient and immediate.
Solution Approach 2:
The system performs preliminary sensor diagnosis and accuracy assessment while the vehicle is still in normal operation, before problems escalate. By continuously comparing sensor data with remote references, the system can identify calibration needs early and alert operators, avoiding the need for urgent repair facility visits.
3Reliability
If sensor data is exchanged between vehicles, then robust cross-vehicle object detection can be achieved, but device complexity increases
Solution Approach 1:
The system uses a universal communication interface and standardized data formats that allow sensor data to be exchanged between different vehicles regardless of manufacturer or model. The same V2V communication infrastructure serves multiple functions including sensor data exchange, confidence score sharing, and collaborative object detection across the vehicle fleet.
Solution Approach 2:
The system implements feedback loops where sensor confidence scores and object detection results are continuously exchanged between vehicles. Remote vehicles provide feedback on target object confidence scores that help refine local sensor interpretations, improving detection robustness through iterative information exchange and validation.
Data Source
AI summary
The present application relates to a method and apparatus for multi vehicle sensor suite diagnosis in a motor vehicle including a receiver operative to receive a remote vehicle sensor data indicative of a location of a target, a sensor operative to collect a host vehicle sensor data indicative of the location of the target, a processor operative to generate a sensor confidence score in response to a comparison of the first remote vehicle sensor data and the host vehicle sensor data, the processor being further operative to perform an assisted driving operation in response to the sensor confidence score, and a transmitter for transmitting the host vehicle sensor data and the sensor confidence score to a first remote vehicle.