Adaptive Forklift Acceleration From Recent Manual Driving Behavior
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Solution Overview
Problem
Materials handling vehicles face challenges in transitioning from manual to semi-automated driving modes, as existing systems rely on fixed acceleration parameters that may not accurately reflect the operator's driving behavior, leading to potential instability or inefficiency, especially when handling varying loads.
Innovation Solution
A method and system that monitor and calculate weighted averages of vehicle drive parameters during recent manual operations to adaptively set acceleration limits for semi-automated driving, considering both directional accelerations and recent driving behavior, allowing for dynamic adjustment based on the calculated averages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed acceleration parameters are used in semi-automated driving mode, then the control system is simple and reliable, but the acceleration control does not accurately reflect the operator's driving behavior, leading to potential instability or inefficiency
Solution Approach 1:
The system performs preliminary monitoring and analysis of manual driving behavior before transitioning to semi-automated mode. The controller stores and analyzes drive parameter data from multiple previous manual operations to establish baseline acceleration patterns, which are then used to configure the semi-automated driving parameters. This preliminary action ensures that the automated system is pre-configured with operator-specific characteristics, improving accuracy without requiring complex real-time adjustments.
Solution Approach 2:
The system implements feedback by continuously monitoring drive parameters during manual operations and using this information to adjust semi-automated driving parameters. The controller compares actual driving behavior against the stored baseline and refines acceleration limits based on observed patterns. This feedback mechanism allows the system to adapt to operator preferences while maintaining controlled complexity through algorithmic processing of monitored data.
2Productivity
If acceleration limits are dynamically adjusted based on recent driving behavior, then the vehicle operation efficiency and safety are improved, but the control system becomes more complex
Solution Approach 1:
The system implements dynamic adjustment of acceleration limits by transitioning from fixed parameters to adaptive parameters that change based on monitored driving behavior. The controller continuously updates acceleration limits by analyzing drive parameters from recent manual operations and adjusting semi-automated parameters accordingly. This dynamic approach allows the system to optimize performance for varying operational conditions while maintaining manageable complexity through systematic parameter adjustment based on observed patterns.
3Adaptability or versatility
If weighted averages of multiple manual operations are calculated to set acceleration parameters, then the adaptability to operator behavior is improved, but the processing time and computational complexity increase
Solution Approach 1:
The system applies partial action by selectively monitoring and analyzing only the most relevant drive parameters from recent manual operations rather than processing all possible operational data. The controller focuses on calculating weighted averages for key acceleration parameters from a limited set of recent operations, sufficient to establish reliable baseline patterns without requiring exhaustive analysis of all historical data. This approach achieves adequate adaptability while minimizing processing time and computational resources.
Data Source
AI summary
Operating a materials handling vehicle includes monitoring, by a controller, a first vehicle drive parameter during a first manual operation of the vehicle by an operator; monitoring, by the controller, the first vehicle drive parameter during a second manual operation of the vehicle by the operator; receiving, by the controller after the first manual operation of the vehicle and the second manual operation of the vehicle, a request to implement a semi-automated driving operation; calculating, by the controller, a first weighted average based on the monitored first vehicle drive parameter during the first manual operation of the vehicle and the monitored first vehicle parameter during the second manual operation of the vehicle; and based at least in part on the calculated first weighted average, controlling, by the controller, implementation of the semi-automated driving operation.