Autonomous Delivery Routing With Vehicle-Specific Indoor Maps
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Solution Overview
Problem
Traditional path modeling methods are ineffective in environments with mixed transportation networks and fail to consider vehicle attributes, such as dimensions and operational capacities, leading to inefficient route selection and inability to adapt to changes in infrastructure.
Innovation Solution
Customized navigation maps are generated for autonomous vehicles, incorporating both outdoor and indoor infrastructure data, along with vehicle attributes, to select optimal routes in real-time, ensuring the vehicle's compatibility and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional path modeling methods are used, then routes can be determined between two points, but vehicle attributes such as dimensions and operational capacities are not considered, leading to incompatible route selections
Solution Approach 1:
The patent applies local quality by creating customized navigation maps tailored to specific vehicle attributes. Each vehicle receives a navigation map that incorporates its unique dimensions, capacity, and operational characteristics, allowing the route selection to be locally optimized for each vehicle's specific qualities rather than using a generic one-size-fits-all approach.
Solution Approach 2:
The system changes parameters by dynamically adjusting route selection based on vehicle-specific parameters such as dimensions, capacity, and operational constraints. The navigation system modifies route parameters in real-time to ensure compatibility with the vehicle's attributes, transforming the static route modeling into a dynamic parameter-driven process.
2Adaptability or versatility
If traditional path modeling methods are used, then outdoor routes can be planned, but indoor infrastructure such as elevators, escalators, and moving sidewalks are not considered
Solution Approach 1:
The patent merges outdoor and indoor navigation systems into a unified customized navigation map. The system combines traditional outdoor path modeling with indoor infrastructure data including elevators, escalators, moving sidewalks, and automatic doors, creating an integrated navigation solution that seamlessly transitions between outdoor and indoor environments.
Solution Approach 2:
The system adds another dimension to traditional path modeling by incorporating vertical transportation elements such as elevators and escalators. This transforms the traditional two-dimensional outdoor route planning into a three-dimensional navigation system that accounts for floor transitions and indoor vertical movement.
3Device complexity
If maximum speed assumptions are made for all vehicles, then route calculation is simplified, but actual travel time predictions become inaccurate due to vehicle-specific operational limits
Solution Approach 1:
The system performs preliminary action by pre-loading vehicle-specific operational parameters such as maximum speed, acceleration, and range limitations into the customized navigation map before route calculation. This allows the route planning algorithm to account for vehicle-specific performance characteristics without adding complex real-time calculations during route determination.
Data Source
AI summary
Customized navigation maps of an area are generated for autonomous vehicles based on a baseline map of the area, transportation systems within the area, and attributes of the autonomous vehicles. The customized navigation maps include a plurality of paths, and two or more of the paths may form an optimal route for performing a task by an autonomous vehicle. Customized navigation maps may be generated for outdoor spaces or indoor spaces, and include specific infrastructure or features on which a specific autonomous vehicle may be configured for travel. Routes may be determined based on access points at destinations such as buildings, and the access points may be manually selected by a user or automatically selected on any basis. The autonomous vehicles may be guided by GPS systems when traveling outdoors, and by imaging devices or other systems when traveling indoors.