Fleet Vehicle Event Definitions Using Risk Profile Patterns
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Solution Overview
Problem
Existing systems for monitoring and managing fleets of vehicles lack an efficient method to create and deploy 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 fleets of vehicles, then vehicle event detection is performed, but the systems lack efficient methods to create and deploy new vehicle event definitions based on risk profiles
Solution Approach 1:
The system automatically creates new vehicle event definitions by analyzing risk profiles and previously detected vehicle events, eliminating the need for manual definition creation. The processor selects relevant events, determines circumstances, and generates definitions autonomously based on identified patterns and risk characteristics
Solution Approach 2:
The system performs preliminary analysis of risk profiles and vehicle event data before deployment to fleet vehicles. By pre-processing and pre-defining event definitions based on historical data and risk assessments, the system prepares actionable definitions in advance for efficient fleet-wide deployment
2Measurement precision
If the system analyzes previously detected vehicle events to create new definitions, then detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the most relevant characteristics and circumstances from previously detected vehicle events that are associated with identified risk profiles. By selecting and extracting only essential features rather than analyzing complete event datasets, the system maintains high detection accuracy while reducing processing time and computational burden
3Reliability
If the system distributes new vehicle event definitions to the fleet, then real-time detection capability is enhanced, but system complexity and deployment overhead increase
Solution Approach 1:
The system creates universal vehicle event definitions that can be applied across the entire fleet of vehicles regardless of specific vehicle types or operating conditions. By developing generalized definitions based on common risk patterns identified through risk profiles, the system ensures consistent and reliable event detection across diverse fleet vehicles without requiring vehicle-specific customization
Solution Approach 2:
The system efficiently distributes identical event definition configurations to multiple fleet vehicles simultaneously. By creating master definition templates and copying them across the fleet rather than individually configuring each vehicle, the system maintains detection reliability while minimizing deployment complexity and overhead
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.


