Autonomous Vehicle Motion Sickness Detection With Physiological Feedback
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Solution Overview
Problem
Motion sickness is a significant issue in autonomous vehicles due to the conflict between vestibular, proprioceptive, and visual senses, leading to nausea and cognitive/emotional discomfort, necessitating early detection to prevent and mitigate symptoms.
Innovation Solution
A method using physiological data from sensors (heart rate, skin conductance, etc.) and vehicle motion data to calculate a motion sickness score, enabling the autonomous vehicle to detect and respond to motion sickness by adjusting dynamics, sensory environments, and visual cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the passenger engages in activities such as reading, texting, or device use, then the passenger can utilize the autonomous vehicle more effectively, but the passenger becomes more susceptible to motion sickness
Solution Approach 1:
The system performs preliminary detection of motion sickness symptoms by continuously monitoring physiological data (heart rate, skin conductance, temperature) before the passenger experiences severe discomfort. This early detection enables the system to alert the passenger or automatically adjust vehicle parameters to prevent motion sickness escalation, allowing the passenger to continue activities like reading or texting with reduced risk.
Solution Approach 2:
The system implements a feedback loop where physiological sensors continuously monitor the passenger's state, the processor analyzes the data to detect motion sickness symptoms, and the system responds by providing alerts or adjusting vehicle operations. This closed-loop feedback enables real-time adaptation to maintain passenger comfort while allowing engagement in various activities.
2Measurement precision
If the system continuously monitors physiological data to detect motion sickness, then early detection and prevention is improved, but the device complexity increases
Solution Approach 1:
The system employs a multi-functional integrated approach where a single processor unit handles multiple tasks: collecting data from various physiological sensors (heart rate, skin conductance, temperature), analyzing the data for motion sickness detection, and controlling vehicle response actions. This universal processing architecture reduces overall system complexity compared to having separate dedicated systems for each function.
Solution Approach 2:
The system combines multiple physiological monitoring functions into a unified detection framework. Instead of separate systems for heart rate monitoring, skin conductance measurement, and temperature sensing, the patent integrates these sensors and their processing into a single motion sickness detection system that correlates data from all sources to improve detection accuracy while managing complexity through centralized processing.
Data Source
AI summary
Techniques described herein include detecting a degree of motion sickness experienced by a user within a vehicle. A suitable combination of physiological data (heart rate, heart rate variability parameters, blood volume pulse, oxygen values, respiration values, galvanic skin response, skin conductance values, and the like), eye gaze data (e.g., images of the user), vehicle motion data (e.g., accelerometer, gyroscope data indicative of vehicle oscillations) may be utilized to identify the degree of motion sickness experienced by the user. One or more autonomous actions may be performed to prevent an escalation in the degree of motion sickness experienced by the user or to ameliorate the degree of motion sickness currently experienced by the user.