Microscopic traffic simulation software allows users to model traffic flow, assess traffic management strategies, and optimize transportation systems for efficiency. However, building a simulation model for a real-world road network is a complex, manual, time-consuming, and error-prone task. GenAI-Enabled Automated Traffic Simulation Management uses Generative AI (GenAI) to automate the preparation of input data, the running of simulations, and the extraction of output results, enabling traffic engineers to focus on the purpose of the simulation rather than the tedious manual work of building the model.
The project maps user text-based scenario descriptions to actual simulation scenarios, with step-by-step validation from the user before execution, by wrapping the INTEGRATION simulation software with a callable API via the Model Context Protocol (MCP) and a web-based interface to a large language model.
The project will deliver a baseline simulation model built with the INTEGRATION microscopic simulation software for a selected freeway corridor or road network; an INTEGRATION API that wraps the simulation software using the Model Context Protocol so it can be called by any large language model; and a web-based graphical user interface that guides users in prompting an LLM to build simulation models and answer questions using Retrieval-Augmented Generation from the INTEGRATION manual. The GenAI system will be validated by comparing GenAI-generated model files against the baseline model, through human-in-the-loop validation, and through real-world deployment with the City of Alexandria.
Universities Involved
Virginia Tech
Principal Investigators
Hesham A. Rakha
Expected Research Outcomes & Impacts
The system has the potential to significantly minimize the learning curve for identifying suitable data sources for traffic simulation and analysis, making traffic modeling and simulation more accessible to users with varying levels of expertise. By automating the preparation of input data, the execution of simulations, and the extraction of results, the GenAI agent equips traffic engineers with essential information for conducting future traffic modeling while reducing manual effort and error.
