Fleet Vehicle Event Definitions Using Risk Profile Feedback
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Solution Overview
Problem
Existing systems for monitoring and managing vehicle fleets lack an efficient method for creating and deploying new vehicle event definitions based on risk profiles, which are essential for detecting and mitigating potential vehicle events.
Innovation Solution
A system and method that utilize risk profiles to select previously detected vehicle events with common characteristics, determine the circumstances leading up to these events, and create new vehicle event definitions. These definitions are then distributed to vehicles in the fleet for detection and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing systems monitor and manage vehicle fleets with basic event detection, then vehicle safety monitoring is provided, but the systems lack efficient methods for creating and deploying new vehicle event definitions based on risk profiles
Solution Approach 1:
The system automatically creates new vehicle event definitions by analyzing risk profiles and detected vehicle events, eliminating the need for manual definition creation. The processor automatically identifies patterns from historical event data and generates updated definitions, allowing the system to self-improve its detection capabilities without external intervention
Solution Approach 2:
The system continuously monitors detected vehicle events and uses this feedback to refine and update event definitions. By analyzing the outcomes of previous detections and associated risk profiles, the system iteratively improves its event definition accuracy and adaptability to new vehicle safety scenarios
2Measurement precision
If the system analyzes vehicle event information to create tailored event definitions, then detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-calculates and stores risk profiles based on historical vehicle event data before they are needed for detection. By preparing risk assessments and event definition candidates in advance, the system reduces real-time processing requirements and enables faster deployment of updated definitions when new patterns are identified
Solution Approach 2:
The system analyzes only the most relevant features and circumstances from historical events when creating new definitions, rather than processing all available data. This selective analysis approach maintains high detection accuracy while reducing computational burden and processing time
3Reliability
If the system distributes new vehicle event definitions to the fleet, then fleet-wide safety monitoring is enhanced, but system coordination and communication overhead increase
Solution Approach 1:
The system creates universal event definitions that can be applied across the entire vehicle fleet, allowing a single definition update to enhance detection capabilities for all vehicles simultaneously. This multi-functional approach ensures consistent safety monitoring across the fleet while minimizing coordination complexity compared to vehicle-specific customization
Data Source
AI summary
Systems and methods for using risk profiles for creating and deploying new vehicle event definitions to a fleet of vehicles are disclosed. Exemplary implementations may: obtain a first risk profile, a second risk profile, and vehicle event characterization information; select individual ones of the previously detected vehicle events that have one or more characteristics in common; determine circumstances for at least a predefined period prior to occurrences of the selected vehicle events; create a new vehicle event definition based on the determined set of circumstances; distribute the new vehicle event definition to individual vehicles in the fleet of vehicles; and receive additional vehicle event information from the individual vehicles in the fleet of vehicles.