Cargo Optimization System Using Vehicle Dynamics and Driver Behavior
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicles lack guidance for optimal placement and securing of cargo, leading to potential movement and shifting during vehicle operation, which can result in safety hazards and damage, due to the absence of technology that considers driver behavior and vehicle dynamics.
Innovation Solution
A system utilizing machine learning models to simulate vehicle and cargo movement, combining vehicle dynamics and cargo characteristics to recommend optimal placement and orientation of cargo within the vehicle, taking into account driver behavior, vehicle operating conditions, and physical properties of the cargo.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cargo is placed in vehicle cargo areas without guidance, then cargo storage is simple and flexible, but cargo may move or shift during vehicle operation causing safety hazards and damage
Solution Approach 1:
The system allows cargo to speak for itself by using computer vision to automatically detect and analyze cargo characteristics, eliminating the need for manual input or complex user interaction while providing intelligent placement recommendations
Solution Approach 2:
The patent replaces complex mechanical cargo securing systems with a computational approach using machine learning models and computer vision to predict cargo movement and provide placement guidance through software rather than hardware
2Object-affected harmful factors
If traditional cargo placement methods are used, then the system is simple, but cargo movement during vehicle operation can cause safety hazards and damage
Solution Approach 1:
The system performs preliminary analysis of cargo characteristics and vehicle dynamics before the journey begins, providing placement recommendations in advance to prevent cargo movement issues rather than addressing them during transport
Solution Approach 2:
The patent introduces an intermediary system consisting of computer vision algorithms and machine learning models that mediate between the cargo characteristics and vehicle dynamics to determine optimal placement, simplifying the decision-making process for users
3Reliability
If cargo placement recommendations are provided based on driver behavior and vehicle dynamics, then cargo security is improved, but computational resources and processing time increase
Solution Approach 1:
The system uses partial action by focusing computational resources on analyzing only the critical factors affecting cargo movement (cargo characteristics, vehicle dynamics, driver behavior) rather than simulating all possible variables, reducing energy consumption while maintaining accuracy
Data Source
AI summary
Systems and methods for optimizing the storage of cargo/use of cargo space or area(s) are provided. A recommendation system can optimize cargo storage in a vehicle by taking into consideration, the characteristics of the cargo itself, as well as driver behavior associated with the vehicle, vehicle characteristics, and vehicle operating dynamics. Based on these considerations, recommendations for optimized packing/storage of the cargo can be provided to a user.