AV User Support via Sentiment Analysis for On-Site Assistance
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Solution Overview
Problem
Existing technologies for supporting users of autonomous vehicles (AVs) are inefficient, particularly in providing on-site assistance during issues such as accidents, where remote customer support may not be as effective as in-person help.
Innovation Solution
A user support platform that utilizes sentiment analysis to determine the emotional state of AV users in real-time, allowing for tailored assistance, including assigning the right support agent and modifying the AV's operational behaviors to better address the user's needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If remote customer support service is used to assist AV passengers, then support can be provided without on-site presence, but the efficiency and effectiveness of assistance is reduced
Solution Approach 1:
The patent introduces an on-site support agent as an intermediary between the AV passenger and the support system. This agent physically presence in the vehicle cabin to provide immediate assistance while being connected to the remote support system through a communication interface, thus combining the benefits of both on-site presence and remote support capabilities
Solution Approach 2:
The patent replaces the purely mechanical approach of having a human driver or on-site mechanic with an automated system that uses sensors, cameras, and AI algorithms to detect passenger states and provide support. The system substitutes physical mechanical intervention with electronic sensing and automated response mechanisms
2Device complexity
If standard remote support protocols are used, then support processes are simple and standardized, but they cannot address individual user needs or emotional states
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and analyzing passenger sentiment and state before support is actually needed. The sentiment analysis and state detection occur proactively throughout the ride, allowing the system to prepare appropriate support responses in advance rather than reacting after problems arise
Solution Approach 2:
The patent introduces dynamic adaptability by using real-time sentiment analysis to adjust support strategies. The system transitions from static, pre-programmed support protocols to dynamic, adaptive responses that change based on the passenger's emotional state and needs, making the support process flexible and personalized
3Adaptability or versatility
If sentiment analysis and real-time monitoring are implemented, then user-specific support can be provided, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the support system into distinct functional modules: sentiment analysis module, state detection module, support agent assignment module, and communication interface module. Each module performs a specific function independently, making the overall complex system manageable through modular design and allowing parallel processing of different tasks
Data Source
AI summary
Assistance can be provided to users of AVs based on user sentiments. A system may receive a request for assistance from a user of an AV (e.g., a passenger of the AV). The system may also receive sensor data that is captured by a sensor suite of the AV from detecting the user, the AV, or another object. The system determines a sentiment of the user based on the sensor data. The system may input the sensor data into a machine learning model and the model outputs information indicating the user's sentiment. The system can determine who, when, or how to service the user's request based on the user's sentiment. The system may assign the user's request to an agent who can provide the assistance. The system can further provide guidance (e.g., suggested content of a conversation with the user) to the agent based on the user's sentiment.