Autonomous Vehicle Map Segments for Area-Specific Navigation Rules
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Solution Overview
Problem
Adapting autonomous vehicles for specific areas is time-consuming and costly due to the need for tailored navigation software, which complicates hardware and increases processing power requirements.
Innovation Solution
A method using a predetermined map with connected segments, each associated with navigation rules and access keys, allows autonomous vehicles to navigate efficiently by integrating area-specific information directly into the map, reducing software complexity and processing power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If navigation software is tailored for each specific area, then the autonomous vehicle can navigate accurately in that area, but the adaptation process becomes time-consuming and costly
Solution Approach 1:
The patent creates a universal map data structure that can be used across multiple areas and vehicles. The map segments and associated rules are designed to be generic yet adaptable, allowing the same navigation software to operate in different areas without area-specific customization. This resolves the contradiction by making the navigation system universally applicable while maintaining area-specific accuracy through the standardized map format.
Solution Approach 2:
The patent uses digital map copies that can be replicated and distributed to multiple vehicles. Instead of customizing software for each vehicle-area combination, the system creates copies of the appropriate map data for each vehicle. This eliminates the time-consuming adaptation process while maintaining navigation accuracy, as each vehicle receives a pre-configured map copy tailored to its operational area.
2Reliability
If navigation software is tailored for each specific area, then the autonomous vehicle can navigate accurately in that area, but the complexity of the software increases
Solution Approach 1:
The patent segments the navigation area into discrete map segments with standardized data structures. Each segment contains specific information about road geometry, navigation rules, and sensor requirements. This segmentation allows the navigation software to handle complex areas through simple, repetitive processing of standardized segments, reducing overall software complexity while maintaining accuracy.
Solution Approach 2:
The patent uses parameter-based configuration where area-specific characteristics are defined through map data parameters rather than hard-coded software logic. By changing map parameters (such as segment geometry, rule sets, and sensor configurations) rather than modifying software code, the system adapts to different areas with reduced complexity. The same software engine processes different areas by loading different parameter sets from the map data.
3Adaptability or versatility
If area-specific information is stored in the navigation software, then the vehicle can adapt to specific areas, but the processing power requirements increase
Solution Approach 1:
The patent extracts area-specific information from the navigation software and stores it in external map data structures. The software engine remains generic and lightweight, while all area-specific details (road geometry, navigation rules, sensor requirements) are stored in the map segments. This separation reduces processing power requirements by moving data storage to external memory rather than requiring complex in-software processing for each area.
Solution Approach 2:
The patent performs preliminary processing of area-specific information during map creation and storage, rather than during runtime navigation. Complex geometric calculations, rule validations, and sensor configurations are pre-computed and stored in the map segments. During actual navigation, the vehicle simply retrieves and follows pre-processed instructions, significantly reducing real-time processing power requirements while maintaining full area adaptability.
4Adaptability or versatility
If navigation software is customized for each area, then the vehicle can handle area-specific characteristics, but the cost of deployment increases
Solution Approach 1:
The patent creates a universal navigation platform that can handle multiple areas with a single software deployment. The standardized map segment structure and rule-based navigation engine allow the same software to be used across different areas by simply loading different map data. This eliminates the need for expensive custom software development for each area, reducing deployment costs while maintaining area-specific handling capabilities.
Solution Approach 2:
The patent enables area-specific handling through parameter configuration rather than software customization. By storing area characteristics as adjustable parameters in the map data (such as road geometry, speed limits, navigation rules), the system can adapt to different areas by loading different parameter sets. This approach dramatically reduces deployment costs compared to custom software development, as parameter configuration is far less expensive than software engineering.
Data Source
AI summary
A method for navigating an autonomous vehicle when driving in an area, includes using a predetermined map of the area for the navigation, wherein the predetermined map comprises a plurality of connected segments, each segment defining a portion of a driving path for the autonomous vehicle to follow. In response to obtaining a mission instruction, the autonomous vehicle is navigated from one point to another point in the area by finding a driving path defined by a number of connected segments of the plurality of connected segment. At least one of the connected segments is associated with at least one of the following predetermined keys: a predetermined access key is accessible for the autonomous vehicle to be allowed to drive in the at least one segment, a predetermined navigation rule defining which sensor to use for the navigation and/or which type of navigation technique to use, a predetermined trigger rule to trigger a work task for the autonomous vehicle.

