Autonomous Vehicle Damage Assessment After Unusual Conditions
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Solution Overview
Problem
Autonomous and semi-autonomous vehicles face challenges in safely operating in unusual environmental conditions and managing malfunctions or collisions, as their automated systems may not function properly in all environments, leading to increased risks.
Innovation Solution
A computer-implemented method for detecting and responding to incidents in autonomous vehicles, which involves monitoring operating data, identifying unusual conditions, determining responses, and implementing actions such as continuing or ceasing operation, communicating with human reviewers, and enabling emergency assistance, while also assessing damage and initiating repairs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles operate in unusual environmental conditions, then serviceability and operational capability are improved, but safety and system reliability deteriorate due to automated systems not functioning properly in all environments
Solution Approach 1:
The system performs preliminary damage assessment and incident detection before the vehicle can be serviced. By automatically detecting incidents, assessing damage, and determining salvageability in real-time, the system prepares necessary information in advance, enabling faster service response when the vehicle stops in unusual environmental conditions.
Solution Approach 2:
The system continuously monitors operating data, detects unusual conditions, and provides feedback about system status and damage assessment. This feedback loop enables the vehicle to communicate its condition to remote servers and service personnel, improving serviceability by providing real-time information about the vehicle's state in unusual environments.
2Ease of manufacture
If the system automatically determines salvageability and initiates repairs, then serviceability is improved, but device complexity increases due to additional monitoring and assessment systems
Solution Approach 1:
The autonomous vehicle performs self-assessment of its own damage and determines its own salvageability. The system automatically monitors its operating data, detects incidents, assesses damage to autonomous operation features, and determines whether it can be salvaged or should be scrapped, eliminating the need for immediate human inspection and improving serviceability.
Solution Approach 2:
A remote server acts as an intermediary between the autonomous vehicle and service personnel. The server receives operating data, performs damage assessment calculations, and communicates salvageability determinations back to the vehicle, reducing the complexity burden on the vehicle itself while maintaining automated serviceability functions.
3Reliability
If the system monitors operating data in real-time to detect incidents, then safety is improved, but use of energy increases due to continuous data processing and communication
Solution Approach 1:
The system processes and transmits damage assessment data rapidly in real-time, then enters lower-power states between incidents. By rushing through the critical detection and communication phases quickly and maintaining continuous monitoring only when necessary, the system improves safety while minimizing energy consumption during normal operation.
Data Source
AI summary
Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.