Entity Allocation Using Complexity Scores for Route Safety
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Solution Overview
Problem
Current methods for allocating entities such as drivers and vehicles to routes lack context, leading to potential safety concerns as they rely solely on performance scores without considering route conditions, and fail to optimally match drivers with vehicles based on skill requirements.
Innovation Solution
The introduction of a complexity score, calculated using vehicle-based alerts and environment-based data, combined with performance scores to provide a context-sensitive view for optimal entity allocation, ensuring entities are matched to routes based on their capabilities and the route's complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If entity allocation is based solely on performance scores, then allocation process is simple, but allocation accuracy and safety are insufficient
Solution Approach 1:
The patent combines multiple scoring systems (performance score, complexity score, and qualifying allocation score) into a unified allocation framework. The qualifying allocation score merges driver performance metrics with route complexity assessment, creating a comprehensive evaluation system that improves allocation accuracy while maintaining systematic organization.
Solution Approach 2:
The complexity score acts as an intermediary element between route characteristics and allocation decisions. By introducing this intermediate metric that quantifies route complexity based on environmental data and vehicle alerts, the system enables more precise matching without requiring direct complex analysis of all route factors during allocation.
2Reliability
If route conditions are not considered in allocation, then allocation process is fast, but safety and appropriateness deteriorate
Solution Approach 1:
The system performs preliminary analysis by pre-calculating route complexity scores based on environmental data, road conditions, and historical vehicle alerts. This advance preparation of route characteristics allows the allocation system to make safety-conscious decisions without time-consuming analysis during the actual allocation process.
Solution Approach 2:
The patent transforms qualitative route conditions (traffic density, road geometry, environmental factors) into quantitative parameters through the complexity score. This parameter transformation enables efficient computational comparison and safety assessment by converting diverse route characteristics into a unified measurable metric.
Data Source
AI summary
Techniques are provided to calculate a “complexity score” (CS) and qualifying allocation score, which aims to address the gap between a performance score, which may represent a driver score of other suitable entity-based performance score. The CS may be calculated based upon the particular agent (e.g. a vehicle, an autonomous mobile robot (AMR), etc.), such as via the use of vehicle-based alerts, other types of alerts, environment-based data, etc., which are collected for specific navigation segments. The CS is then combined with the performance score to provide a qualifying allocation score, which is a context-sensitive view of the performance score. This context-sensitive view of the performance score may then be utilized for a determination regarding how to allocate the most well-suited entity (a driver, vehicle, AMR, etc.) to a subsequent route that includes the navigation segments.