Next Generation Modeling for Connected and Autonomous Vehicles (NGM - CAV)

Goal and Objectives

This project aims to develop the next-generation models for connected and automated vehicles covering a wide range of autonomy levels, connectivity levels, and scenarios. NGM connects real-world trajectory data with microscopic traffic simulation, allowing researchers to study human-driven, automated, connected, and heavy vehicles in a common environment.

About NGM
NGM is a research-oriented traffic simulation tool built on Eclipse SUMO, Python, and TraCI. It provides an integrated workflow for calibrating behavioral models from observed trajectories and applying the resulting parameters in configurable traffic simulations.
The graphical interface allows users to define the network, traffic demand, vehicle composition, behavioral models, communication settings, and simulation outputs without manually creating every SUMO configuration file.

The key innovations associated with the proposed research approach are:

1. Integration of Different Modeling Frameworks Associated with Different ADAS and ADS Components and CAVs
2. Flexible Simulation Scenario Creation
3. Useful Data and Visualization Generation for Traffic Impact Studies
4. Robustness

Project Team

Dr. Samer Hamdar	Dr. Alireza Talebpour	Dr. Hani Mahmassani
Lead Principal Investigator	Co-Principal Investigator	Co-Principal Investigator
Professor, Department of Civil and Environmental Engineering, The George Washington University.	Assistant Professor, Department of Civil and Environmental Engineering, The University of Illinois Urbana-Champaign.	Professor, Department of Civil and Environmental Engineering, Northwestern University.