Autonomous Vehicle Passenger Feedback Triggered by Driving Events
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Solution Overview
Problem
Existing feedback systems for autonomous vehicles often collect feedback after a trip is completed, missing timely and accurate insights from passengers.
Innovation Solution
A real-time feedback system that monitors triggering circumstances, display requirements, and data collection parameters to prompt passengers for feedback during the trip, using a feedback system integrated with the vehicle's computing devices to analyze road conditions and passenger interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If feedback is collected after trip completion, then feedback processing is simplified, but feedback timeliness and accuracy deteriorate
Solution Approach 1:
The system performs preliminary actions by monitoring triggering circumstances and preparing feedback requests before the trip ends. The feedback request is presented to the passenger during the trip when the triggering circumstance occurs, ensuring timely collection while the event is fresh in the passenger's mind, rather than waiting until trip completion.
Solution Approach 2:
The system implements continuous feedback monitoring during the trip by detecting triggering circumstances (such as disengagement from autonomous mode, presence of road users, or trip state changes) and immediately presenting relevant feedback requests. This creates a real-time feedback loop that captures passenger responses at the moment of experience, improving both timeliness and accuracy.
2Loss of information
If feedback requests are displayed frequently, then feedback data completeness improves, but passenger annoyance increases
Solution Approach 1:
The system applies local quality by customizing feedback requests based on specific triggering circumstances. Different feedback questions are presented depending on the context (e.g., disengagement events, road user interactions, trip phase), ensuring that feedback is relevant and necessary rather than generic and repetitive. This targeted approach improves data completeness while maintaining passenger engagement.
Solution Approach 2:
The system uses partial action by selectively presenting feedback requests only when specific triggering circumstances occur, rather than continuously or at fixed intervals. This ensures comprehensive coverage of important events without overwhelming the passenger with excessive feedback demands, balancing data completeness with user experience.
3Measurement precision
If real-time feedback monitoring is implemented, then feedback accuracy improves, but computational resource consumption increases
Solution Approach 1:
The system extracts and monitors only specific triggering circumstances that are relevant to feedback collection (disengagement events, road user presence, trip state changes) rather than continuously analyzing all vehicle parameters. This selective monitoring approach maintains high feedback accuracy by capturing critical moments while reducing unnecessary computational overhead and energy consumption.
Data Source
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AI summary
The disclosure relates collecting feedback from passengers of autonomous vehicles. For instance, that a triggering circumstance for triggering a feedback request has been met may be determined. The triggering circumstance may include a driving event, a presence of other road users, or a trip state. A display requirement and data collection parameters for the feedback request are identified based on the determination. The display requirement defines when the feedback request is displayed and the data collection parameters identify information that the feedback request is to collect. The feedback request is provided for display based on the display requirement and data collection parameters. In response, feedback from a passenger of the autonomous vehicle is received and stored for later use.