Load-Aware Vehicle Scheduling for No-Stop Gradient Nodes
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Solution Overview
Problem
Existing vehicle control methods do not effectively account for the impact of loading on a vehicle's performance and operational cost, leading to inefficiencies and increased mechanical wear, especially in challenging topographies and when vehicles need to climb steep gradients or travel downhill.
Innovation Solution
A loading-aware scheduling method that distinguishes between loaded and empty vehicles by defining specific subsets of planning nodes where loaded vehicles cannot stop, thereby optimizing vehicle movements and reducing unnecessary contention and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a loaded vehicle is allowed to stop at any planning node, then the vehicle can wait for optimal conditions or traffic, but the vehicle experiences increased energy consumption, mechanical wear, and operational costs
Solution Approach 1:
The planning nodes are segmented into two distinct subsets: a first subset where loaded vehicles are prohibited from stopping, and a second subset where stopping is permitted. This segmentation creates differentiated stopping zones that optimize energy consumption by restricting stops in energy-inefficient locations while allowing stops in appropriate locations.
Solution Approach 2:
Different stopping rules are applied to different spatial locations (planning nodes) based on their local characteristics. The first subset of planning nodes is identified as locations where stopping loaded vehicles would be particularly energy-consuming or operationally inefficient, while the second subset contains locations where stopping is acceptable. This local differentiation optimizes overall system energy efficiency.
2Reliability
If a loaded vehicle stops and then accelerates from stationary position, then the vehicle can wait for safe movement conditions, but the vehicle experiences rapid fuel consumption and stress on mechanical components
Solution Approach 1:
The system performs preliminary identification of planning nodes where stopping would lead to harmful effects. By pre-defining the first subset of planning nodes where loaded vehicles cannot stop, the system prevents situations where vehicles would need to accelerate from stationary positions under heavy load, thereby avoiding mechanical stress and rapid fuel consumption before the stopping decision is even made.
Solution Approach 2:
The invention applies preliminary anti-action by prohibiting stops at certain planning nodes before the vehicle arrives there. This preventive measure stops the harmful sequence (stopping → waiting → high-stress acceleration) from occurring in the first place, rather than trying to mitigate the effects after they occur.
3Use of energy by moving object
If the scheduling method distinguishes between loaded and empty vehicles with different stopping rules, then the vehicle performance and energy consumption are optimized, but the scheduling system complexity increases
Solution Approach 1:
The complex problem of load-aware scheduling is simplified by segmenting the planning nodes into two clear subsets with distinct stopping rules. This segmentation transforms a potentially complex continuous optimization problem into a more manageable discrete classification problem, where each planning node is simply categorized as either allowing or prohibiting stops for loaded vehicles.
Solution Approach 2:
The system changes the parameter of stopping permission from a continuous or fine-grained control to a discrete binary parameter (allowed/not allowed) at each planning node. This parameter simplification reduces computational complexity while still achieving the goal of optimizing energy consumption by preventing stops at unfavorable locations.
Data Source
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 and is movable to other nodes along edges 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 of the planning nodes at which no loaded vehicle is allowed to stop; obtaining predefined routes of the vehicles; and scheduling 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 is defined on the basis of topographical information.