AGV Route Determination Using Real-Time Traffic Simulation
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Solution Overview
Problem
Automated guided vehicles in production plants often face challenges in determining the shortest route due to overlapping driving routes and the influence of other vehicles, leading to potential collisions and inefficiencies, as existing methods do not effectively account for real-time traffic and congestion.
Innovation Solution
A method and system that determine the shortest time route for automated guided vehicles through real-time simulation, considering current positions and simulation times of all vehicles, and prioritizing routes based on simulation times to optimize movement and avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple automated guided vehicles operate in the same workspace with overlapping routes, then vehicle utilization and productivity are improved, but the risk of collisions and route conflicts increases
Solution Approach 1:
The system implements real-time feedback mechanisms where each AGV continuously reports its position, speed, and status to the central controller. The controller processes this feedback and dynamically adjusts route assignments and speed commands to prevent collisions while maintaining high utilization of multiple vehicles in shared workspaces.
Solution Approach 2:
The route determination system dynamically adapts to changing conditions by continuously monitoring the positions and states of all AGVs. When conflicts or potential collisions are detected, the system dynamically reassigns routes or adjusts speed profiles in real-time, allowing multiple vehicles to operate safely in overlapping paths without rigid predetermined routing.
2Loss of time
If the shortest path route is selected for automated guided vehicles, then moving distance and time are reduced, but the influence of other vehicles and traffic congestion is not considered leading to potential collisions
Solution Approach 1:
The central controller acts as an intermediary between individual AGVs and the route determination system. It receives real-time position and status information from all vehicles, calculates optimal routes considering the positions of other AGVs, and issues adjusted route commands. This intermediary function ensures that shortest-path optimization does not lead to collisions by coordinating vehicle movements system-wide.
Solution Approach 2:
The system performs preliminary route planning that anticipates potential conflicts before they occur. By calculating routes based on current positions of all AGVs and predicting future trajectories, the system proactively assigns routes that avoid potential collisions while still achieving near-optimal travel times, rather than reacting to conflicts after they arise.
3Productivity
If real-time simulation is performed to determine the shortest time route considering all vehicles, then moving time and traffic efficiency are improved, but the computational complexity and processing requirements increase
Solution Approach 1:
The route determination process is segmented into discrete steps: (1) receiving position information from all AGVs, (2) performing real-time simulation to calculate moving times for candidate routes, (3) comparing simulation results, and (4) selecting the optimal route. This segmentation allows the complex calculation to be broken into manageable computational tasks that can be executed efficiently by the controller.
Solution Approach 2:
The system changes parameters dynamically based on real-time conditions. Instead of using fixed route parameters, the simulation calculates moving times based on current positions, speeds, and predicted trajectories of all AGVs. This parameter adaptation allows the system to optimize for actual traffic conditions while keeping computational requirements manageable through focused calculation on relevant variables.
Data Source
AI summary
A method of determining a route of a main automated guided vehicle includes: determining whether a work is assigned to the main automated guided vehicle; extracting a first and second control points of the work when the work is assigned to the main automated guided vehicle; determining whether multiple routes exist from the first control point to the second control point; determining a single route as a final route of the main automated guided vehicle when the number of routes from the first control point to the second control point is one; predicting a moving time of the main automated guided vehicle for all candidate routes and determining a shortest time route among the candidate routes as the final route of the main automated guided vehicle, when the number of the routes from the first control point to the second control point is equal to or greater than two.