Working Machine Rollover Prediction Using Load and Terrain Gradients
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Solution Overview
Problem
Current rollover risk assessment systems for load transporting working machines are inadequate as they do not effectively account for changes in load weight and terrain gradients, leading to insufficient warning times for drivers to prevent rollover incidents.
Innovation Solution
A method that utilizes ground topographic data and on-board load weighting systems to determine a working machine's maximal allowed ground gradient, predicting rollover risk by comparing approaching terrain gradients to this limit, and providing warnings to drivers or autopilots to adjust their path accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current rollover risk assessment systems use only current working machine inclination angle and speed for determining rollover risk, then the system complexity is low, but the warning time is insufficient and the reliability is reduced
Solution Approach 1:
The system performs preliminary detection of terrain gradients using ground topographic data before the working machine actually enters the dangerous area. By extracting ground gradient information from topographic maps and comparing it with the machine's current position and heading, the system provides advance warning of potential rollover risks, allowing sufficient time for the driver to take preventive actions such as changing path or reducing speed.
Solution Approach 2:
The system introduces ground topographic data as an intermediary element between the machine's current state and the rollover risk assessment. By obtaining terrain information from external topographic maps and processing it through the control unit, the system creates a more comprehensive risk assessment that combines machine parameters with environmental factors, thereby improving reliability without requiring complex additional sensors on the machine itself.
2Adaptability or versatility
If the system determines maximal allowed ground gradient based on load weight information, then the adaptability to different loading conditions is improved, but the device complexity increases due to additional weighing systems
Solution Approach 1:
The system achieves adaptability to different load conditions by utilizing load weight information that can be obtained from existing on-board weighing systems or from the loading device's control unit. This multi-functional approach allows the same ground gradient threshold determination mechanism to work for both loaded and unloaded machine conditions, eliminating the need for separate assessment systems while improving adaptability.
Solution Approach 2:
The system implements feedback by continuously monitoring the relationship between the actual ground gradient and the maximal allowed ground gradient determined from load weight information. When the actual gradient approaches or exceeds the threshold, the system provides feedback warnings to the driver, creating a closed-loop system that adapts to varying load conditions and provides appropriate warnings based on the current loading state.
3Loss of time
If the system provides early warning before the working machine enters the risk area, then the warning time is improved, but the difficulty of detecting and measuring the risk increases
Solution Approach 1:
The system performs preliminary risk detection by comparing the working machine's current position and heading with pre-stored ground topographic data. By determining the ground gradient at the machine's current location and comparing it with the maximal allowed gradient, the system identifies potential risk areas before the machine enters them, providing advance warning while using straightforward computational methods based on existing sensor data.
Solution Approach 2:
The system replaces complex mechanical terrain sensing with electronic data processing by utilizing ground topographic maps and the machine's position information from existing GPS or navigation systems. This substitution transforms the physical challenge of real-time terrain measurement into an electronic information processing task, reducing the difficulty of detection while maintaining early warning capability.
Data Source
AI summary
A method is provided for predicting a risk for rollover of a working machine for load transportation. The method includes: obtaining ground topographic data of a geographical area located close to the working machine from a ground topographic detection system; extracting a ground gradient from the ground topographic data; obtaining weight information of the load being currently transported by means of an on-board load weighting system or by receiving load information originating from the device that loaded the load being currently transported; determining a current maximal allowed ground gradient for the working machine based on the weight information; and predicting a risk for working machine rollover if the working machine approaches a geographical area including a ground gradient exceeding or being close to the current maximal allowed ground gradient for the working machine.