18338418. ENTITY ALLOCATION FOR NAVIGATED ROUTES simplified abstract (Intel Corporation)
Contents
ENTITY ALLOCATION FOR NAVIGATED ROUTES
Organization Name
Inventor(s)
Raghavendra Bhat of Bangalore (IN)
Pravin Chander Chandran of Fremont CA (US)
Sean Lawrence of Bangalore (IN)
ENTITY ALLOCATION FOR NAVIGATED ROUTES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18338418 titled 'ENTITY ALLOCATION FOR NAVIGATED ROUTES
The patent application provides techniques to calculate a "complexity score" (CS) and qualifying allocation score to bridge the gap between a performance score and entity-based performance score.
- The CS is determined based on specific agent data, such as vehicle-based alerts or environment-based data, collected for navigation segments.
- The CS is combined with the performance score to create a qualifying allocation score, offering a context-sensitive view of the performance score.
- This context-sensitive view helps in allocating the most suitable entity (driver, vehicle, AMR, etc.) to subsequent routes.
- Potential Applications:**
- Autonomous vehicles - Fleet management systems - Logistics and supply chain operations
- Problems Solved:**
- Enhancing route optimization - Improving allocation decisions - Increasing efficiency in transportation systems
- Benefits:**
- Enhanced decision-making - Optimal resource allocation - Improved overall performance
- Commercial Applications:**
Optimizing fleet operations in transportation companies to reduce costs and improve efficiency.
- Prior Art:**
Readers can explore prior patents related to route optimization, performance scoring, and resource allocation in transportation systems.
- Frequently Updated Research:**
Stay updated on advancements in autonomous vehicle technology, fleet management systems, and navigation algorithms.
- Questions about the Technology:**
1. How does the complexity score impact resource allocation decisions? 2. What are the key factors considered in calculating the qualifying allocation score?
Original Abstract Submitted
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.
