Vehicle Camera Display Adaptation Using Multi-Source Driving Triggers
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Solution Overview
Problem
Existing camera image presentation systems in vehicles lack dynamic and customizable features, failing to adapt to various driving scenarios and workflows, which can impact user experience and safety.
Innovation Solution
A computer system in the vehicle determines triggers such as user inputs, vehicle activities, workflow activities, object activities, and environmental conditions to dynamically change camera image presentation properties, such as zoom, tilt, and container size, to optimize image data display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If camera image presentation is made dynamic and customizable to adapt to various driving scenarios, then user experience and safety are improved, but device complexity increases
Solution Approach 1:
The camera image presentation system dynamically adjusts display properties (such as zoom level, tilt, and container size) based on detected triggers from multiple sources including user inputs, vehicle activities, workflow activities, object activities, and environmental conditions. This dynamic adaptation allows the system to provide context-appropriate camera views without requiring multiple fixed configuration systems, thereby improving adaptability while managing complexity through a unified dynamic control approach.
2Adaptability or versatility
If multiple trigger types are monitored to enable dynamic camera image presentation, then adaptability and user experience are enhanced, but device complexity and processing requirements increase
Solution Approach 1:
The system implements a universal trigger monitoring mechanism that handles multiple types of triggers (user inputs, vehicle activities, workflow activities, object activities, and environmental conditions) through a unified processing framework. This multi-functional approach allows diverse trigger sources to be monitored and processed by the same system architecture, enhancing customizability while avoiding the need for separate specialized systems for each trigger type.
Solution Approach 2:
The computer system acts as an intermediary that receives and processes triggers from multiple diverse sources, then translates these triggers into appropriate camera image presentation adjustments. This intermediary role consolidates the complexity of monitoring multiple trigger types within a single processing layer, simplifying the overall system architecture while maintaining the ability to respond to various driving scenarios.
3Productivity
If camera presentation properties are dynamically changed based on triggers, then situational awareness and operational efficiency are improved, but loss of time for processing and response may occur
Solution Approach 1:
The system pre-establishes the relationship between trigger types and corresponding camera presentation property adjustments during system setup and operation. By having predetermined response protocols for different trigger categories, the system can quickly map detected triggers to appropriate presentation changes without requiring complex real-time decision-making, thereby improving operational efficiency while minimizing processing delays.
Data Source
AI summary
Dynamic camera image presentation in a vehicle is described herein. In an example, a computer system presents, on a display of a vehicle, first image data generated by a camera of the vehicle. The first image data is based at least in part on a first presentation property. The computer system determines a trigger to change the first presentation property and a second presentation property associated with a type of the trigger. The computer system presents, on the display, second image data generated by the camera. The second image data is presented based at least in part on the second presentation property.