Vehicle Movement Scheduling With Load-Aware No-Stop Nodes
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Solution Overview
Problem
Existing vehicle control methods fail to efficiently schedule vehicle movements considering the impact of loading on performance and operational cost, particularly in environments with varying weights and topographies, leading to increased energy consumption, mechanical wear, and traffic contention.
Innovation Solution
A method and traffic planner that schedules vehicle movements by defining subsets of planning nodes where loaded vehicles cannot stop, enforcing no-stopping conditions, and prioritizing loaded vehicles, while leveraging efficient scheduling algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If loaded vehicles are allowed to stop at any planning node, then vehicle scheduling flexibility is improved, but energy consumption and mechanical wear increase due to unnecessary stopping and starting maneuvers
Solution Approach 1:
The patent applies local quality by creating differentiated stopping rules: loaded vehicles are prohibited from stopping at uphill planning nodes (first subset) while allowing stops at other nodes. This localized restriction针对性地 addresses the energy consumption problem at critical locations without completely eliminating scheduling flexibility elsewhere in the system.
Solution Approach 2:
The patent implements preliminary action by pre-defining the first subset of planning nodes where loaded vehicles cannot stop, based on topographical information identified in advance. This allows the scheduling algorithm to proactively plan routes that avoid problematic stopping locations rather than reacting to energy consumption issues during execution.
2Loss of energy
If loaded vehicles are prioritized and given no-stopping conditions, then operational cost and energy consumption are reduced, but device complexity and scheduling algorithm complexity increase
Solution Approach 1:
The patent applies parameter changes by introducing a loading state parameter that modifies vehicle behavior rules. When a vehicle is detected as loaded, it automatically receives restricted stopping permissions at uphill nodes. This parameter-based approach allows the same scheduling framework to handle different vehicle states without requiring completely separate algorithms.
Solution Approach 2:
The patent segments the set of all planning nodes into two subsets: the first subset where loaded vehicles cannot stop (uphill nodes) and the second subset where stops are permitted. This segmentation simplifies the scheduling logic by creating clear, location-based rules rather than requiring complex real-time optimization for each possible stopping scenario.
3Loss of energy
If vehicle scheduling considers loading state and topography, then energy consumption and mechanical wear are minimized, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary computation by pre-identifying and storing the first subset of planning nodes where loaded vehicles cannot stop, based on topographical data. This preprocessing step converts complex topographical analysis into simple lookup operations during scheduling, significantly reducing real-time computational requirements while maintaining energy optimization.
Solution Approach 2:
The patent applies local quality by focusing computational resources on identifying critical uphill locations rather than analyzing all possible vehicle maneuvers throughout the entire environment. This localized approach concentrates processing effort where it has the greatest impact on energy consumption while leaving other areas with simpler, faster scheduling logic.
4Object-generated harmful factors
If no-stopping conditions are enforced for loaded vehicles at specific nodes, then mechanical wear and fuel consumption are reduced, but productivity and vehicle throughput may decrease
Solution Approach 1:
The patent uses preliminary action by pre-planning routes that avoid requiring loaded vehicles to stop at uphill nodes. The scheduling algorithm proactively assigns alternative routes or timing that bypass problematic locations, ensuring continuous movement and maintaining productivity while preventing mechanical wear from repeated stopping and starting.
Solution Approach 2:
The patent applies dynamics by making stopping permissions dynamic based on vehicle loading state and location. Rather than imposing static restrictions, the system adaptively adjusts allowed stopping behavior according to real-time vehicle conditions and environmental factors, optimizing both mechanical wear reduction and throughput maintenance.
Data Source
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AI summary
A method of scheduling movements of a plurality of vehicles, wherein each vehicle occupies one node in a shared set of planning nodes (311, 312, …) and is movable to other nodes along edges (351, 352) between pairs of the nodes, and the vehicle has a time-variable internal state of being either loaded or not-loaded. The method comprises: defining a first subset (L) of the planning nodes at which no loaded vehicle is allowed to stop; obtaining predefined routes (371, 372) of the vehicles; and scheduling (216) the movements of the vehicles along said predefined routes while enforcing a no-stopping condition in the first subset of the planning nodes. In some embodiments, the first subset (L) is defined on the basis of topographical information (360).