Remote Vehicle Speed Planning Using Ruleset Control Nodes
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Solution Overview
Problem
Current remote-controlled vehicle systems lack the ability to dynamically determine and adapt to changing conditions for optimal control speed, relying on manual operator input that is inefficient and unable to capitalize on potential time-saving opportunities.
Innovation Solution
A system that generates a control speed plan based on rulesets applied to control nodes within a viewing window, adjusting to changing conditions by incorporating additional nodes and their associated rulesets to optimize speed profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual operator input is used to control vehicle speed, then the system is simple to operate, but the system cannot dynamically adapt to changing conditions for optimal speed control
Solution Approach 1:
The control system automatically determines optimal control speeds by applying rulesets to control nodes within a viewing window without requiring continuous manual operator input. The system serves itself by autonomously adjusting speed profiles based on real-time operating conditions, eliminating the need for operators to manually calculate or request speed changes while maintaining simplicity of operation.
Solution Approach 2:
The system dynamically adjusts control speeds by incorporating additional control nodes and their associated rulesets as conditions change. The viewing window and speed profiles are continuously updated based on current operating parameters, allowing the system to adapt to changing conditions while maintaining a manageable level of complexity through automated processing.
2Measurement precision
If the system incorporates more control nodes and rulesets to improve speed control accuracy, then the control precision improves, but the computational complexity increases
Solution Approach 1:
The control system divides the operating environment into discrete control nodes within a viewing window, each associated with specific rulesets. This segmentation allows the system to process complex conditions in manageable units, determining optimal speeds for each node independently while maintaining overall system accuracy without overwhelming computational complexity.
3Productivity
If the system dynamically adjusts control speed based on real-time conditions, then productivity improves, but the system complexity increases
Solution Approach 1:
The system pre-establishes rulesets for various control nodes that define optimal speeds under different conditions. When operating conditions change, the system simply applies the appropriate pre-defined rulesets rather than calculating optimal speeds from scratch, enabling rapid dynamic adjustment that improves productivity while keeping the control architecture manageable through reuse of predefined logic.
Data Source
AI summary
Methods and systems for selection of a control speed for a remote-controlled vehicle based on rulesets applied to control nodes within a viewing window. In embodiments, a viewing window including control nodes, each having a having ruleset defining operating conditions associated therewith, may be determined. The ruleset for a control node may define operating limitations (e.g., speed limitations, orientation limitations, etc.) at the control node. In embodiments, a control speed plan for the viewing window may be generated based on the operating conditions for each control node within the current viewing window based on the limitations associated with each control node. The control speed plan may include an optimal control speed at each control node within the viewing window and a speed profile indicating an acceleration or deceleration curve to be followed through each of the optimal control speeds in the control speed plan when executing the control speed plan.