Virtual Driver Models for Autonomous Vehicle Pedestrian Communication
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Solution Overview
Problem
Autonomous vehicles lack the ability to effectively communicate with external observers, such as pedestrians and human drivers, due to the absence of a human driver, which is crucial for safe and efficient traffic flow.
Innovation Solution
Generating virtual models, such as augmented or virtual reality 3D models of a driver, that can interact with external observers through gestures, audio, and visual cues, and utilizing encryption techniques to ensure secure communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a human driver is present in a conventional vehicle, then real-time interactions with external observers can occur, but in autonomous vehicles the absence of a human driver eliminates this communication capability
Solution Approach 1:
The patent creates virtual models that copy human driver appearance, gestures, and communication behaviors. These virtual models are rendered in the driver's seat area to visually replicate a human presence, enabling external observers to perceive and interact with the autonomous vehicle as if a human driver were present, thereby resolving the communication capability loss while maintaining autonomous operation
Solution Approach 2:
The virtual model acts as an intermediary between the autonomous vehicle's control system and external observers. It translates internal vehicle states and intentions into human-understandable visual cues, gestures, and expressions, facilitating communication without requiring actual human presence in the vehicle
2Ease of operation
If virtual models are displayed to external observers, then communication capability is restored, but system complexity increases due to rendering and encryption requirements
Solution Approach 1:
Instead of implementing complex real-time motion capture and physical puppeteering systems, the patent uses computational rendering to create visual copies of human drivers. This software-based approach achieves realistic communication effects through algorithms that generate appropriate gestures and expressions based on vehicle sensor data and context, reducing hardware complexity while maintaining communication capability
Solution Approach 2:
The system dynamically adjusts virtual model parameters such as gesture amplitude, response timing, and expression intensity based on detected external observer characteristics and traffic conditions. This adaptive parameter tuning optimizes communication effectiveness while managing computational resources efficiently, balancing complexity with performance
Data Source
AI summary
Systems and methods for interactions between an autonomous vehicle and one or more external observers include virtual models of drivers the autonomous vehicle. The virtual models may be generated by the autonomous vehicle and displayed to one or more external observers, and in some cases using devices worn by the external observers. The virtual models may facilitate interactions between the external observers and the autonomous vehicle using gestures or other visual cues. The virtual models may be encrypted with characteristics of an external observer, such as the external observer's face image, iris, or other representative features. Multiple virtual models for multiple external observers may be simultaneously used for multiple communications while preventing interference due to possible overlap of the multiple virtual models.