Augmented Vehicle Load Visualization for Weight Distribution Guidance
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Solution Overview
Problem
Traditional methods for indicating vehicle loading issues, such as misloading or unbalanced weight distribution, lack intuitiveness and sufficient information, leading to potential handling degradation and safety concerns.
Innovation Solution
A system that combines load data from vehicle sensors with live video data to generate an augmented reality environment, providing visual instructions on how to properly load the vehicle by identifying objects and correlating their loads, and guiding users to redistribute them for optimal weight distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional warning lights or dashboard indicators are used to alert drivers of loading issues, then the system remains simple and low-cost, but the information provided is insufficient and not intuitive enough for drivers to understand and correct the problem
Solution Approach 1:
The patent transitions from two-dimensional dashboard warning lights to three-dimensional augmented reality overlays that appear to float in the driver's field of view through the windshield. Weight indicators, axle load information, and loading guidance are projected as virtual objects in spatial dimension, providing intuitive visual feedback about vehicle loading conditions without requiring complex additional hardware interfaces
Solution Approach 2:
The patent introduces a camera as an intermediary device that captures the physical vehicle and loading environment, then processes this visual data to generate augmented reality overlays. The camera acts as a mediator between the physical loading state and the driver's perception, translating sensor data into visually intuitive representations that guide proper loading without directly modifying the vehicle's existing simple warning systems
2Ease of operation
If augmented reality overlays with detailed loading information are implemented, then driver understanding and correction ability improve, but the system complexity and cost increase
Solution Approach 1:
The system enables drivers to self-diagnose and self-correct loading problems by providing them with clear visual information about axle loads and proper weight distribution. The augmented reality overlays guide drivers to move specific items to achieve balanced loading, allowing them to independently resolve loading issues without requiring external assistance or complex manual procedures
Solution Approach 2:
The patent replaces traditional mechanical warning systems (physical gauges, indicator lights) with optical and computational systems. Cameras capture visual data, processors analyze loading conditions, and displays project augmented reality information, substituting mechanical indication methods with electronic and optical technologies that provide more informative and intuitive feedback
3Reliability
If real-time weight indicators and loading guidance are provided through augmented reality, then vehicle safety and performance improve, but information processing requirements and computational load increase
Solution Approach 1:
The system performs preliminary analysis of loading conditions by capturing images and processing weight data before the driver needs to take action. The augmented reality overlays pre-compute and display the optimal loading configuration, allowing drivers to make informed decisions about item placement without requiring complex real-time calculations during the loading process itself
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture are disclosed to generate an augmented environment including a weight indicator for a vehicle. An example disclosed system includes a camera to capture image data including a first location of an object in a vehicle, processor circuitry to execute instructions to generate a map of loads on the vehicle, and a user interface to present an augmented environment identifying the first location of the object and a load correlated with the object, the load correlated with the object based on the map of loads.