Windshield Crack Cause Detection for Autonomous Vehicles
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Solution Overview
Problem
Autonomous vehicles lack the capability to automatically detect and classify the cause of windshield damage, such as impacts from stones or other objects, which is necessary for reporting and further investigation, especially in the absence of a human driver.
Innovation Solution
The system employs interior microphones and sensors to detect sound waves and determine the cause of windshield damage, using an electronic processor to analyze sensor information and execute appropriate mitigation actions, including notifying operators or authorities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to detect windshield damage in autonomous vehicles, then damage detection capability is improved, but the ability to automatically determine the cause of damage deteriorates
Solution Approach 1:
The system segments the damage detection task into two distinct functions: sensors detect the physical damage to the windshield, while interior microphones capture acoustic information about the cause. This segmentation allows each component to specialize in one aspect, with the processor integrating both data streams to achieve complete damage characterization without overloading a single sensor system.
Solution Approach 2:
Interior microphones serve as an intermediary device that bridges the gap between physical damage detection and cause identification. The microphones capture sound waves generated by impact events, providing acoustic evidence that mediates between the sensor data (confirming damage) and the need to identify the cause, enabling automated determination without human intervention.
2Productivity
If autonomous vehicles operate without human drivers, then operational efficiency is improved, but the ability to investigate and respond to damage causes deteriorates
Solution Approach 1:
The autonomous vehicle performs self-diagnosis and self-investigation of damage causes through the integrated sensor-microphone system. The vehicle automatically captures acoustic data, processes it to identify impact causes, and generates reports without requiring human drivers or external investigators, enabling the system to serve itself in damage assessment functions.
Solution Approach 2:
The system establishes a feedback loop where damage sensors trigger microphone activation, which then provides acoustic feedback to the processing system. This feedback mechanism enables the autonomous vehicle to continuously monitor and respond to damage events, automatically adjusting its investigation and response actions based on real-time acoustic evidence from the environment.
3Measurement precision
If multiple sensors and microphones are integrated to detect and classify damage, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The electronic processor is designed as a universal component that handles multiple functions: it processes data from various sensor types (accelerometers, gyroscopes, cameras) and integrates acoustic data from microphones. This multi-functional processor reduces overall system complexity by consolidating data fusion and analysis capabilities in a single device rather than requiring separate specialized systems for each sensor type.
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
Enables autonomous vehicles to automatically detect, classify, and respond to windshield damage, ensuring compliance with legal requirements and facilitating further investigation or necessary actions without human intervention.
Implementation Method 1
a microphone positioned to detect sound waves inside the vehicle
Data Source
AI summary
Detecting and classifying damage to a vehicle. One example system includes a microphone positioned to detect sound waves inside the vehicle, one or more sensors positioned on the vehicle and configured to sense a characteristic of a windshield of the vehicle, and an electronic processor communicatively coupled to the one or more sensors and the microphone. The electronic processor is configured to receive sensor information from the one or more sensors and to receive an electrical signal from the microphone. The electronic processor is configured to determine, based on the sensor information, whether a crack event has occurred. The electronic processor is configured to, in response to determining that a crack event has occurred, determine a cause of the crack event based on the electrical signal received from the microphone. The electronic processor is configured to execute a mitigation action based on the cause of the crack event.