Autonomous Vehicle Routing Graph Constraints for Mixed Fleet Paths
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Solution Overview
Problem
Existing autonomous vehicle routing systems face inefficiencies due to the need for distinct routing graphs for various vehicle types, roadway conditions, and business policies, which leads to costly data management and cumbersome modifications as conditions change.
Innovation Solution
A general-purpose routing graph is used, with routing graph modification data applied to generate a constrained routing graph, allowing for efficient routing of different types of autonomous vehicles under varying conditions and policies without the need for frequent graph updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distinct routing graphs are created for various vehicle types, roadway conditions, and business policies, then routing accuracy and suitability for specific conditions is improved, but data management complexity and storage costs increase significantly
Solution Approach 1:
The patent merges multiple distinct routing graphs into a single unified routing graph that serves all vehicle types, roadway conditions, and business policies. Instead of maintaining separate graphs for each condition, the system consolidates all routing data into one graph structure, significantly reducing data management complexity and storage requirements while maintaining the ability to handle diverse routing scenarios through a shared infrastructure
Solution Approach 2:
The unified routing graph is designed to be universal and multi-functional, capable of serving multiple vehicle types (autonomous vehicles, human-driven vehicles, bicycles, pedestrians), various roadway conditions (construction zones, weather conditions, traffic patterns), and different business policies simultaneously. This single graph structure replaces the need for multiple specialized graphs, achieving both routing accuracy and data management efficiency
2Reliability
If routing graphs are updated frequently to reflect changing roadway conditions, then routing reliability under current conditions is improved, but computational overhead and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing routing information in the unified graph during off-peak periods or in advance. Routing data is prepared and organized beforehand, allowing the system to quickly retrieve and apply pre-computed routes when conditions change, rather than performing complex calculations in real-time when updates are needed
Solution Approach 2:
The unified routing graph implements dynamic adaptability, allowing the system to efficiently respond to changing roadway conditions by selectively updating only the affected portions of the graph rather than recalculating the entire structure. This dynamic approach maintains routing reliability under current conditions while minimizing computational overhead and processing time
3Adaptability or versatility
If multiple constrained routing graphs are maintained for different vehicle types, then routing suitability for specific vehicle capabilities is improved, but data storage costs and management burden increase
Solution Approach 1:
The patent combines the need for vehicle-specific, condition-specific, and policy-specific routing graphs into a single unified routing graph. Instead of storing multiple copies of routing data for different vehicle types (autonomous vehicles, human-driven vehicles, bicycles, pedestrians), the system maintains one comprehensive graph that accommodates all vehicle types and conditions, dramatically reducing data storage volume and management burden
Solution Approach 2:
The unified routing graph achieves universality by being applicable to all vehicle types and conditions simultaneously. The graph structure is designed to handle diverse routing requirements through a single data structure, eliminating the need for separate constrained routing graphs for each vehicle type while maintaining routing suitability for specific vehicle capabilities
Data Source
AI summary
Various examples are directed to routing autonomous vehicles. A processor unit accesses first routing graph modification data and second routing graph modification data. The first routing graph modification data based at least in part on first vehicle capability data describing a first type of autonomous vehicle and the second routing graph modification data based at least in part on second vehicle capability data describing a second type of autonomous vehicle. The processor unit accesses routing graph data describing a plurality of graph elements and generates a first route for a first autonomous vehicle of the first type based at least in part on the first routing graph modification data and the routing graph data. The processor unit also generates a second route for a second autonomous vehicle of the second type based at least in part on the second routing graph modification data and the routing graph data.