Cloud Motion Planning for Fleet-Specific Vehicle Route Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack efficient methods for managing permissions and authorizing access to services for fleets of autonomous vehicles, particularly in dynamic environments where real-time adjustments are necessary.
Innovation Solution
The system implements a processor-based solution that accesses a data store of candidate motion planning systems, selects the appropriate system based on vehicle or fleet identifiers, and generates planned routes considering physical capabilities and operating restrictions, while also managing permissions and access through a web authentication token.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a cloud-based system is used to manage motion planning for autonomous vehicle fleets, then system efficiency and adaptability are improved, but device complexity and permission management overhead increase
Solution Approach 1:
The patent introduces a cloud-based motion planning system as an intermediary between autonomous vehicles and route optimization services. The cloud system receives trip service requests, selects appropriate motion planning systems based on vehicle identifiers, generates candidate trajectories, and returns planned routes. This intermediary architecture centralizes complex planning logic, improving individual vehicle efficiency while managing system complexity through service abstraction.
Solution Approach 2:
The cloud-based system serves multiple functions: it acts as an authentication service verifying web authentication tokens, a motion planning system generating trajectories, a simulation system evaluating routes, and a permission management service. By consolidating these diverse functions into a single multi-functional platform, the system improves overall productivity while managing complexity through integrated service design.
2Reliability
If web authentication tokens are used for access management, then permission control and security are improved, but system complexity and authentication overhead increase
Solution Approach 1:
The authentication system operates autonomously by automatically verifying web authentication tokens without requiring manual intervention. When a motion planning system or simulation system requests access, the cloud system self-service validates the token, checks permissions against the data store, and grants or denies access automatically. This self-service approach improves security reliability while minimizing authentication overhead.
Solution Approach 2:
Web authentication tokens are issued in advance with embedded permissions and authorizations. Rather than performing complex permission checks during each operation, the system performs preliminary authentication by validating the pre-issued token. This preliminary action establishes trust and permissions upfront, improving security while reducing real-time authentication complexity.
3Adaptability or versatility
If multiple candidate motion planning systems are maintained in the data store, then system adaptability and vehicle-specific optimization are improved, but data store complexity and selection overhead increase
Solution Approach 1:
The data store organizes motion planning systems with vehicle-specific or fleet-specific identifiers, creating local quality in the data structure. Each motion planning system is tailored to specific vehicle characteristics or fleet requirements, allowing the cloud system to select the most appropriate planning system based on the vehicle identifier in the trip service request. This local quality approach improves adaptability while managing data store complexity through organized, identifier-based retrieval.
Data Source
AI summary
Methods and systems for generating a planned path for a vehicle are disclosed. Upon receiving a trip service request, a processor will access a data store containing multiple candidate motion planning systems, each of which is associated with at least one vehicle or fleet. The processor will identify a starting point and a destination for the trip service request, and it will use an identifier for the vehicle or its fleet to select, from the candidate systems, a motion planning system. The processor will use the functions of the selected motion planning system to generate candidate trajectories for the first vehicle from the starting point to the destination in a high definition map. The processor will select a planned route from the candidate trajectories, and it will output trip instructions to cause the vehicle to move along the planned route.