Vehicle-Human Gesture Interface for Autonomous Road Interaction
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Solution Overview
Problem
Autonomous vehicles and vehicles with ADAS lack the ability to effectively communicate with human road users, which is crucial for enhancing safety and interaction in various driving scenarios.
Innovation Solution
Implementing a method for communication between vehicles and human road users using machine learning to detect human gestures and interactions, and a man-machine interface to respond with human-perceivable signals, enabling vehicles to perform driving operations based on these interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles rely on electronic communication means, then communication efficiency between vehicle systems is improved, but ability to communicate with human road users deteriorates
Solution Approach 1:
The patent introduces a human-machine interface (MMI) as an intermediary that translates between electronic communication systems and human communication modalities. The MMI detects human gestures and communications, converts them into electronic signals for the autonomous vehicle system, and translates system responses back into human-perceivable forms, enabling bidirectional communication between autonomous vehicles and human road users.
Solution Approach 2:
The system copies human communication behaviors by detecting human gestures and reproducing appropriate responses through the MMI. The autonomous vehicle learns to mimic human communication patterns by observing and responding to human road users' gestures, eye contact, and body language, enabling naturalistic interaction that bridges the gap between electronic systems and human users.
2Measurement precision
If autonomous vehicles use machine learning to detect human communication, then communication accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the communication detection task into multiple specialized machine learning models, each trained to detect specific aspects of human communication such as gestures, eye contact, body orientation, and verbal cues. This modular approach improves detection accuracy for each specific communication modality while managing overall system complexity through divided responsibility among specialized components.
Solution Approach 2:
The MMI system serves multiple functions: detecting human gestures, interpreting communication intent, generating appropriate responses, and coordinating with the autonomous vehicle's driving decisions. This multi-functional design consolidates what could be separate complex systems into a single integrated interface, reducing overall system complexity while maintaining high communication detection accuracy.
3Reliability
If vehicles respond to human gestures, then safety interaction is improved, but response time may be reduced
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and pre-processing sensor data for signs of human communication attempts before they become critical. The MMI is constantly scanning for gestures, eye contact, and other communication cues, preparing the system to respond immediately when communication is detected, thereby reducing actual response time while maintaining safety.
Solution Approach 2:
The system implements feedback loops where the MMI continuously monitors human road user responses to vehicle actions and adjusts subsequent communications accordingly. This real-time feedback enables the system to learn from interactions, improve response accuracy, and optimize response timing to balance safety requirements with efficient communication.
Data Source
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AI summary
A method for communication between a vehicle and a human road user, the method comprises: determining, by a vehicle processing module, and based on sensed information that sensed by at least one vehicle sensor, to interact with a human road user; and interacting with the human road user by generating, by a man machine interface, one or more representations of one or more human gestures.