Petri-net Message Processor for Human-in-the-loop Simulation
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Solution Overview
Problem
Existing multiple-entity scenario simulations are challenging to set up accurately and efficiently, especially when incorporating human interactions, as they require complex programming and sequencing of activities, making them time-consuming and costly.
Innovation Solution
Incorporating a Petri-net message processor function that routes messages between activity node functions to enable human interaction within the simulation, allowing for realistic exchanges and triggering simulation activities based on user responses, thereby integrating humans into automated multiple-entity scenario simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple-entity scenario simulations are completely automated and programmed for a particular purpose, then the simulation accuracy and sequence control are improved, but the development time and cost increase significantly
Solution Approach 1:
The simulation system is segmented into independent activity node functions (ANFs) that can be developed and configured separately. Each ANF represents a discrete simulation activity that can be independently programmed, tested, and deployed, reducing overall development complexity and time while maintaining simulation accuracy through modular assembly.
Solution Approach 2:
The Petri-net message processor function serves multiple purposes: it routes messages between ANFs, manages simulation state transitions, coordinates human participant interactions, and triggers simulation activities. This multi-functional component reduces the need for separate control mechanisms, thereby reducing development time while maintaining reliable sequence control.
2Adaptability or versatility
If human participants are integrated into automated multiple-entity scenario simulations, then training effectiveness and response time monitoring are improved, but the system complexity and programming difficulty increase
Solution Approach 1:
The Petri-net message processor function acts as an intermediary between human participants and the automated simulation system. It receives messages from ANFs intended for human participants, routes them appropriately, and processes human responses back into the simulation workflow. This intermediary layer simplifies the interface complexity by providing a standardized communication protocol while enabling effective human integration for training purposes.
3Reliability
If extensive programming is used to ensure proper sequencing and parallel activities with accurate timing, then the simulation fidelity is improved, but the ease of setup and modification deteriorates
Solution Approach 1:
Activity node functions are pre-configured with their specific activities, message routing requirements, and timing parameters before being assembled into the simulation. The Petri-net message processor is pre-programmed with standard routing logic and state transition rules. This preliminary configuration reduces setup time and simplifies modifications, as individual ANFs can be independently adjusted without reprogramming the entire simulation system while maintaining faithful sequence control.
Data Source
AI summary
Mechanisms for incorporating a human into an automated multiple-entity scenario simulation are disclosed. A Petri-net message processor function (PMPF) receives a first Petri-net message from a source activity node function (ANF). The Petri-net message includes a simulation activity identifier that identifies a first simulation activity. The PMPF routes the first Petri-net message to a first ANF based on the simulation activity identifier. The first ANF receives the first Petri-net message and provides a message to a user based on the first Petri-net message. A response is received from the user. A second Petri-net message is generated based on the response and is communicated to a destination ANF to trigger a second simulation activity by the destination ANF.