Collective VR Navigation Using Graph Vertex Traffic Potentials
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Solution Overview
Problem
Existing VR navigation systems are individually based, which can lead to issues in group settings as they do not account for the presence and movement of other users, potentially causing congestion and reducing the overall user experience.
Innovation Solution
A method for collective navigation in VR devices that uses a graph model of a navigable space to determine optimal paths while minimizing segment lengths and vertex traffic potentials, dynamically adjusting vertex traffic potentials to guide users and avoid crowded areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If individually based navigation is provided to each VR user, then each user receives personalized navigation information, but congestion occurs in group settings due to lack of coordination among users
Solution Approach 1:
The patent combines individual navigation needs with group coordination by integrating real-time user location data and movement patterns. The system merges multiple individual navigation requests into a coordinated group navigation system that assigns paths considering overall traffic flow, thus maintaining personalized guidance while preventing congestion through collective optimization.
Solution Approach 2:
The system implements continuous feedback loops by monitoring real-time user positions, path selections, and crowd density. This feedback mechanism allows the navigation system to dynamically adjust individual paths based on current group movements, ensuring that personalized navigation information remains effective while adapting to changing traffic conditions to maintain overall flow efficiency.
2Loss of time
If users are guided through shortest paths in a navigable space, then navigation efficiency is improved, but crowded areas are not avoided leading to congestion
Solution Approach 1:
The patent applies dynamic path planning that continuously adapts to changing crowd conditions. Instead of static shortest paths, the system dynamically recalculates navigation routes based on real-time user distribution and movement patterns. This allows users to deviate from traditional shortest paths when congestion is detected, balancing navigation efficiency with crowd avoidance through continuous adaptation.
Solution Approach 2:
The system changes the optimization parameters from purely distance-based shortest paths to a multi-parameter optimization that includes crowd density, user distribution, and predicted traffic flow. By modifying the path selection criteria to consider multiple factors beyond minimal distance, the system achieves navigation efficiency while actively avoiding congested areas through parameter-based route optimization.
Data Source
AI summary
A computer-executed method is disclosed for collective navigation of distributed virtual reality (VR) devices. The method obtains a source vertex and a destination vertex for a VR device. The source vertex and the destination vertex include vertices of a graph model of a navigable space having a plurality of vertices. The vertices represent a point within the navigable space and the plurality of edges represent a path segment between two corresponding vertices. A subset of possible vertices, selected from the plurality of vertices, is determined for a navigable path. A vertex traffic potential is determined for each vertex of the subset of possible vertices. The navigable path, including one or more consecutive path segments selected to minimize both segment path lengths and vertex traffic potentials, is determined from the source vertex to the destination vertex.