Vehicle Anomaly Detection via Crowd-Assisted Prognostics
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Solution Overview
Problem
Drivers may not notice issues with their own vehicles, such as open fuel/charge doors or burnt-out lights, while driving, and alerting another driver can be difficult without causing distractions or intruding on privacy.
Innovation Solution
A vehicle-based computing system with a processor and external sensors detects anomalies in nearby vehicles, attempts direct communication, and broadcasts identifying characteristics and anomalies if direct communication fails, allowing for timely notification of the affected driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a driver attempts to alert another driver of a vehicle issue while both vehicles are moving, then the driver experiencing the issue can be notified, but distraction issues and safety risks increase
Solution Approach 1:
The patent replaces the mechanical system of direct human-to-human communication (yelling, gesturing) with an automated electronic communication system. The detecting vehicle's processor automatically transmits anomaly data to the affected vehicle through wireless communication, eliminating the need for drivers to physically engage with each other and thereby removing distraction and safety risks while ensuring reliable notification delivery.
2Loss of information
If a driver attempts to engage with another driver to notify them of an issue, then the affected driver can be alerted, but privacy intrusion increases
Solution Approach 1:
The affected vehicle's processor autonomously determines whether received anomaly data pertains to its own vehicle by comparing identifying characteristics. The system automatically filters and processes information without requiring the driver's active engagement or decision-making, thereby delivering necessary notifications while respecting driver privacy and reducing unnecessary interactions.
3Measurement precision
If a vehicle systematically scans and monitors nearby vehicles for anomalies, then detection accuracy improves, but energy consumption increases
Solution Approach 1:
The processor is configured to scan for nearby vehicles and detect anomalies at periodic intervals rather than continuously. The system activates external sensors and processing functions at scheduled times to gather necessary data, then enters lower-power states between scans. This periodic operation maintains adequate anomaly detection accuracy while significantly reducing the energy consumption of sensors and processors compared to continuous monitoring.
Data Source
AI summary
A system includes a vehicle-processor in communication with an external vehicle sensor, wherein the processor is configured to detect another vehicle within a predefined proximity. The processor is further configured to instruct the external vehicle sensor to scan a characteristic of the another vehicle, responsive to the detecting. Also, the processor is configured to determine if the characteristic includes an anomaly, responsive to the scan and notify the driver of the another vehicle of the anomaly, responsive to the determination.