Self-Driving Vehicle Mishap Detection via Multi-Sensor Fusion
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Solution Overview
Problem
Self-driving vehicles (SDVs) face challenges in detecting and responding to vehicular mishaps, especially in scenarios where affected vehicles are unable to communicate their distress due to mechanical failures or lack of cellular coverage, and there is a lack of monitoring infrastructure in rural areas.
Innovation Solution
Equipping SDVs with sensors such as LIDAR, video systems, audio systems, and vibration sensors to detect mishaps and assess their severity, allowing them to autonomously report incidents to authorities and provide data for emergency response and investigation, even in areas without communication infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If SDVs use sensors to detect mishaps in vehicles unable to communicate, then detection capability is improved, but device complexity increases
Solution Approach 1:
The patent applies multi-functionality by enabling SDV sensors to serve dual purposes: their primary function for autonomous navigation and collision avoidance, and a secondary function for detecting and assessing mishaps in other vehicles. The same LIDAR, video, audio, and vibration sensors used for self-driving also detect abnormal vibrations, sounds, and visual indicators of vehicle mishaps, eliminating the need for dedicated detection hardware.
Solution Approach 2:
The system applies self-service by using the SDV's own onboard sensor suite and processing capabilities to detect, assess, and respond to mishaps in other vehicles. The SDV's processors analyze sensor data to determine mishap confidence levels and trigger appropriate responses, leveraging the vehicle's existing computational resources rather than requiring external monitoring infrastructure.
2Loss of time
If SDVs autonomously report mishaps to authorities, then response time is improved, but loss of time for verification increases
Solution Approach 1:
The system applies preliminary action by performing confidence level assessment and preliminary verification of mishap detection before triggering the autonomous response. The processors evaluate sensor data against predetermined confidence thresholds, and only when the confidence level exceeds the threshold does the system autonomously contact authorities. This preliminary verification step ensures reliability while maintaining rapid response times.
Solution Approach 2:
The system applies feedback by using multiple sensor inputs (LIDAR, video, audio, vibration) that continuously monitor and provide feedback about the detected vehicle's condition. The processors analyze this feedback stream to determine whether the detected anomalies constitute a genuine mishap, adjusting the confidence level dynamically based on corroborating evidence from multiple sensor modalities.
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 timely and accurate reporting of vehicular mishaps, ensuring prompt assistance and improved investigation capabilities, regardless of the affected vehicle's communication status or location.
Implementation Method 1
Equipping SDVs with sensors such as LIDAR, video systems, audio systems, and vibration sensors to detect mishaps
Implementation Method 2
Equipping SDVs with sensors such as LIDAR, video systems, audio systems, and vibration sensors to detect mishaps
Data Source
AI summary
A self-driving vehicle (SDV) ameliorates a vehicular mishap incurred by a second vehicle. At least one sensor on a first SDV detects a second vehicle that has been involved in a vehicular mishap. One or more processors determine a confidence level L, which is a confidence level of a mishap assessment accuracy of determining that the second vehicle has been involved in the vehicular mishap. In response to the confidence level L exceeding a predetermined value, the SDV executes an amelioration action to ameliorate a condition of the second vehicle that has been involved in the vehicular mishap.