Vehicle Load AR Overlay for Intuitive Weight Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for indicating vehicle loading issues, such as exceeding axle weight ratings or improper weight distribution, lack intuitiveness and effectiveness, often requiring drivers to frequently check displays, which can lead to misloading and performance problems.
Innovation Solution
An augmented reality environment is generated using load data from sensors and live video feed, providing visual and auditory feedback through lights and sounds to guide drivers in properly loading vehicles and trailers by correlating load data with object locations and conditions, using a processor to control external lights and sound sources based on load thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional display methods are used to indicate vehicle loading issues, then drivers can obtain load information, but the method lacks intuitiveness and requires frequent checking which reduces efficiency
Solution Approach 1:
The system provides real-time visual feedback through augmented reality overlays that display load status, weight distribution, and threshold violations directly in the driver's field of view. This continuous feedback eliminates the need for frequent display checks and enables intuitive understanding of loading conditions, thereby improving both information delivery and loading efficiency
Solution Approach 2:
The patent transitions from traditional 2D display screens to 3D augmented reality visualization that overlays load information directly onto the physical environment. By projecting virtual images of load status, weight indicators, and warning messages into the driver's real-world view, the system creates an immersive dimensional experience that enhances intuitiveness and reduces cognitive load
2Ease of operation
If augmented reality environment is generated with real-time video and load data, then loading intuitiveness is improved, but device complexity increases
Solution Approach 1:
The system integrates multiple functions into a single augmented reality interface: displaying weight values, indicating load thresholds, showing weight distribution, providing visual warnings, and guiding proper loading all through one unified AR overlay. This multi-functionality approach improves loading intuitiveness while managing system complexity by consolidating features rather than multiplying separate systems
Solution Approach 2:
The augmented reality display acts as an intermediary layer between the complex sensor systems and the driver. Rather than exposing the driver to raw sensor data and complex system operations, the AR interface translates multiple data streams into intuitive visual representations, effectively mediating between system complexity and user simplicity
3Measurement precision
If load data is correlated with object locations using camera and sensors, then loading accuracy is improved, but measurement and detection difficulty increases
Solution Approach 1:
The system creates a virtual copy of the physical loading environment through augmented reality, where digital representations of objects are overlaid with their corresponding load data. By correlating camera-identified objects with sensor-measured weights through spatial mapping, the system achieves precise load measurement and object correlation while simplifying the detection process through visual matching rather than complex identification
Data Source
AI summary
Methods and apparatus to generate an augmented environment including a weight indicator for a vehicle are disclosed herein. An example apparatus disclosed herein includes memory including stored instructions, a processor to execute the instructions to generate a map of loads on a vehicle based on load data associated with a sensor of the vehicle, determine a load condition of the vehicle based on the map of loads, correlate a first load of the map of loads with an object identified using live video data received from a camera, and generate an augmented environment identifying at least one of a location of the object, the first load correlated with the object, or the load condition.