Ride Control Simulation Using Stochastic Dispatch Events
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Solution Overview
Problem
Current ride system control simulations fail to accurately account for stochastic events such as variable passenger load times, safety check times, and dispatch times, leading to inaccurate outputs and negative impacts on ride system operations.
Innovation Solution
A simulation environment that utilizes randomly selected values from data distributions to model stochastic events between the stopping and dispatch times of passenger vehicles, allowing for more accurate simulation of ride control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional simulation methods are used for ride control systems, then the simulation process is simple and quick, but the accuracy of simulation results deteriorates due to failure to account for stochastic events
Solution Approach 1:
The patent creates a virtual copy of the ride control system through a computer model that replicates the physical system's behavior. This digital twin approach allows stochastic events to be simulated without modifying the actual physical system, thereby improving simulation accuracy while maintaining operational simplicity.
Solution Approach 2:
The patent introduces stochastic parameters (random variables) into the simulation model to represent real-world uncertainties in passenger loading, safety checks, and dispatch times. By changing from deterministic to probabilistic parameters, the simulation accurately captures the variability inherent in ride operations.
2Measurement precision
If stochastic events are incorporated into the simulation, then the accuracy of operational metrics improves, but the computational complexity and time required for simulation increases
Solution Approach 1:
The patent implements stochastic simulation selectively for specific critical processes (passenger loading, safety checks, dispatch) rather than entire system modeling. This partial application of stochastic methods provides sufficient accuracy for operational metrics while limiting computational overhead and execution time.
Solution Approach 2:
The patent pre-generates random number sequences and stochastic event parameters before simulation execution. This preliminary preparation allows the actual simulation to run efficiently using pre-computed probabilistic data, reducing real-time computational requirements while maintaining accuracy.
Data Source
AI summary
In some implementations, a ride control simulation system may receive a request to simulate a ride control system controlling a movement of a passenger vehicle on a ride system, wherein the request includes vehicle information regarding the passenger vehicle and ride system information regarding the ride system. The ride control simulation system may execute, based on the request, a computer model to simulate the ride control system controlling the movement of the passenger vehicle on the ride system. Executing the computer model comprises randomly selecting values from one or more data distributions. The computer model is executed using the first value, the second value, and the third value as inputs. The ride control simulation system may cause an adjustment to an operation of the ride system based on a result of executing the computer model.