AI Ride Head Tracking for Dynamic Attention-Based Motion Control
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Solution Overview
Problem
Existing amusement park rides with pre-programmed profiles fail to dynamically adjust to passenger interactions and attention, leading to unrealistic experiences and limited engagement.
Innovation Solution
A ride system that utilizes attention tracking and AI algorithms to predict passenger attention and adjust the ride's dynamic profile, including content rendering and vehicle movement, based on real-time passenger interactions and physics models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-programmed profiles are used to control ride vehicle movements and content rendering, then the system operation is simplified and reliable, but the adaptability to passenger interactions and attention is reduced
Solution Approach 1:
The system implements feedback mechanisms by tracking passenger head position, eye gaze direction, and attention focus in real-time, then using this information to dynamically adjust ride vehicle movements and content rendering. Sensors capture passenger responses which are fed back to the control system to modify the ride experience dynamically.
Solution Approach 2:
The patent transitions from static pre-programmed profiles to dynamic control systems that continuously adapt ride parameters based on real-time passenger attention data. The ride vehicle movements and content rendering are no longer fixed but dynamically adjusted according to passenger engagement levels and attention focus.
2Ease of operation
If pre-programmed profiles are used for ride vehicle movements, then the system is easier to operate, but the realism of passenger experience is reduced
Solution Approach 1:
The system enables self-service operation by automatically tracking passenger attention and autonomously adjusting ride parameters without requiring manual intervention. The control system processes sensor data and makes real-time decisions about vehicle movements and content rendering independently.
Solution Approach 2:
The patent replaces traditional mechanical control systems with sensor-based tracking and computational algorithms. Instead of manual operation or fixed mechanical profiles, the system uses optical sensors, cameras, and AI algorithms to detect passenger attention and generate dynamic control commands.
3Use of energy by moving object
If all content is rendered regardless of passenger attention, then the processing is simplified, but the energy consumption increases
Solution Approach 1:
The system applies local quality optimization by rendering content selectively based on where the passenger is actually looking. Instead of uniformly rendering all content in the field of view, the system identifies the foveal attention region and prioritizes rendering high-detail content only in that specific area, while using lower detail or procedural generation for peripheral regions.
Solution Approach 2:
The patent implements partial rendering action by determining which portions of content are actually visible and relevant to the passenger's current attention focus. The system renders only the necessary portions of the virtual environment at high quality, while using simplified or procedural content for areas outside the passenger's attention zone.
Data Source
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AI summary
A ride system may include a ride vehicle that supports a passenger and an attention tracker to determine a current direction of attention of the passenger. The ride system may also include a control system for maintaining an environment of the passenger. Maintaining the environment may include determining a set of content to be incorporated into the environment based at least in part on the current direction of attention.