FACT SHEET

September 2022

DEVELOPING FUTURE TRAFFIC 

MANAGEMENT SYSTEMS 

USING HYBRID TWINS

Traffic management in metropolitan areas poses distinct challenges. Faced with 

congested city streets shared by pedestrians, bicyclists, electric-scooter riders, and 

drivers, traffic managers must find new ways to maintain smooth and safe traffic flow. 

Traffic managers can harness the data collected by electronic devices that connect to 

HYBRID TWINS FOR TRAFFIC MODELING 

Transportation researchers already employ 

virtual twins and digital twins to mimic 

real-world experiences, but the concept of a 

hybrid twin is still relatively new. A hybrid twin is 

a simulation model that combines a virtual twin 

and a digital twin.

Virtual twins are physics-based simulation 

models; they simulate how objects or systems 

behave using prior domain knowledge. However, 

virtual twins sometimes differ from their 

real-world counterparts and cannot accurately 

and efficiently simulate large environments. A 

digital twin gathers and analyzes data from 

sensors (such as those in vehicles, traffic 

cameras, radar devices, and infrastructure) 

to mimic what is happening in the selected 

real-world environment. Digital twins provide 

real-time data-based information and allow 

researchers to model scenarios, make 

predictions, and test mitigation strategies.(1)

A hybrid twin, combining the concepts of 

virtual twins and digital twins, leverages both 

domain knowledge and data to provide a more 

realistic simulation environment.(2) More accurate 

simulations offer the following advantages:

• Facilitate test scenarios quickly and safely.

• Advance understanding of urban traffic 

modeling, computation, and simulation.

• Lead to more informed decisionmaking 

as traffic managers predict, optimize, and 

control traffic flow.

urban traffic management system that will help improve traffic safety, mobility, and 

reliability. To explore the possibilities of this advanced traffic management system, 

the research team at Columbia University is creating a hybrid twin of an area of New 

York City.

the internet, infrastructural sensors, other 

devices or systems, and communications 

networks in the Internet of Things 

(IoT) to transform urban streets. The 

Exploratory Advanced Research 

(EAR) Program of the Federal 

Highway Administration (FHWA) and 

the Cyber Physical Systems program at 

the National Science Foundation (NSF) 

are supporting a 3-yr research project 

that leverages the IoT to develop an 

© 2022 Columbia University. 

The researchers are using cameras to capture traffic data.
FACT SHEET

DEVELOPING FUTURE TRAFFIC MANAGEMENT 

SYSTEMS USING HYBRID TWINS September 2022 

EXPLORATORY ADVANCED RESEARCH

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For example, the hybrid-twin system could 

assist with incident management. When a traffic 

incident occurs, the system could propose 

options, such as detours or road closures, to 

reduce the impact on traffic flow.

In the project titled “Hybrid Twins for 

Urban Transportation: From Intersections 

to Citywide Management,” the Columbia 

University research team is developing a 

hybrid twin that integrates artificial intelligence, 

machine-learning algorithms, edge-cloud 

computing, and advanced communications 

networks to simulate and predict traffic states 

for various traffic scenarios. The hybrid twin 

will operate parallel and in realtime with the 

real-world environment it mimics.

A NEW LEVEL OF TRAFFIC MANAGEMENT

In the first phase of the project, the researchers 

are using artificial intelligence to extract data 

from sensors to develop the digital twin. The 

researchers also are integrating a traffic simulator, 

a communications network simulator, and a 

three-dimensional autonomous driving simulator. 

With the traffic simulator, the researchers can 

generate each vehicle and let each one move in 

its own network. 

Eventually, the researchers plan to integrate 

FHWA’s CARMA Platform to simulate how 

vehicles generate messages and communicate 

with other vehicles.(3)

 Based on those messages, 

the system will be able to interact with vehicles.

The researchers are deploying the Cloud 

Enhanced Open Software Defined Mobile 

Wireless Testbed for City-Scale Deployment 

(COSMOS) testbed in the West Harlem 

neighborhood streets of New York City, NY, to 

evaluate and validate the traffic management 

system.(4)

 The COSMOS testbed, a component of 

the NSF Platforms for Advanced Wireless Research, 

will soon cover a corridor of 20 city blocks.

In the second phase of the project, the 

researchers will begin adding real-time data 

to the simulation environment to create the 

hybrid twin. The hybrid twin will incorporate 

real-time data and domain knowledge to make 

more accurate predictions, such as traffic state 

© 2022 Google® MapsTM. Annotations by Columbia University to show project deployment. Photos © 2022 Columbia University. 

Phase 1 deployment.
FACT SHEET

DEVELOPING FUTURE TRAFFIC MANAGEMENT 

SYSTEMS USING HYBRID TWINS September 2022 

EXPLORATORY ADVANCED RESEARCH

3

estimations—the speed and density of traffic 

in an area—every 5 min. The system will use 

existing models within the simulator to make 

those predictions.

By assimilating data acquired from infrastructure 

and in-vehicle sensors for traffic modeling, 

prediction, and management, the hybrid-twin 

system will be able to monitor surrounding 

traffic, send safety warnings to connected 

vulnerable users, and provide learning-based 

controls to traffic lights and automated vehicles. 

The system thereby can help improve traffic 

flow and capacity, increase road safety, and 

reduce emissions. 

“The vision is that one day we will have a 

data-driven traffic management center to 

improve safety, mobility, and reliability. The 

traffic management center in the research 

project will have access to data that today’s 

centers do not,” said Rachel James of FHWA’s 

Office of Safety and Operations Research and 

Development. “If we can manage the system 

more effectively, everyone benefits.”

KNOWLEDGE SHARING

The research project includes an education plan 

to expand underrepresented populations’ access 

to and participation in computer science and 

engineering programs. The researchers have 

developed an outreach program to explain 

transportation concepts to teachers and 

students in grades K–12 in the New York City 

Public Schools located in Harlem. 

© 2022 Columbia University. 

The researchers are integrating CARLA® simulation images and 

Simulation of Urban MObilityTM (SUMO) traffic simulations in the 

COSMOS testbed.(5,6)

© 2022 Columbia University. 

This diagram shows the components of the hybrid twin along with 

the data flow between the components.

© 2022 Columbia University. 

Three different nodes with advanced wireless communications 

capabilities are being used in the COSMOS testbed. 

“If we can manage the system more 

effectively, everyone benefits.”

—Rachel James, Ph.D. 

Research Civil Engineer, FHWA Office of Safety and 

Operations Research and Development.
FACT SHEET

DEVELOPING FUTURE TRAFFIC MANAGEMENT 

SYSTEMS USING HYBRID TWINS September 2022 

EXPLORATORY ADVANCED RESEARCH

REFERENCES

1. Rudskoy, A., I. Ilin, and A. Prokhorov. 2021. 

“Digital Twins in the Intelligent Transport Systems.” 

Transportation Research Procedia 54: 927–935. 

https://www.sciencedirect.com/science/article/pii/

S235214652100332X, last accessed May 18, 2022.

2. Chinesta, F., E. Cueto, E. Abisset-Chayanne, J. 

L. Duval, and F. E. Khaldi. 2020. “Virtual, Digital 

and Hybrid Twins: A New Paradigm in Data-Based 

Engineering and Engineered Data.” Archives of 

Computational Methods in Engineering 27, no. 1: 

105–134.

3. FHWA. 2022. “CARMA Products” (web page). 

https://highways.dot.gov/research/operations/

CARMA-products, last accessed April 25, 2022. 

4. National Science Foundation. n.d. “COSMOS: Cloud 

Enhanced Open Software Defined Mobile Wireless 

Testbed for City-Scale Deployment” (website). https://

www.cosmos-lab.org/, last accessed August 15, 2022.

5. CARLA Team. 2022. “CARLA: Open-source 

simulator for autonomous driving research” (website). 

https://carla.org/, last accessed August 15, 2022.

6. Eclipse Foundation. n.d. Simulation of Urban 

MObility (software). Version 1.14.1. https://www.

eclipse.org/sumo/, last accessed August 15, 2022.

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Recommended citation: 

Federal Highway Administration, 

Developing Future Traffic Management Systems 

Using Hybrid Twins (Washington, DC: 2022) 

https://doi.org/10.21949/1521929.

FHWA-HRT-22-089

HRTM-20/09-22(WEB)E

CONTACT

For more information about this EAR Program 

project, contact Rachel James, FHWA Office 

of Safety and Operations Research and 

Development, at 202-493-3205 

(email: rachel.james@dot.gov).

LEARN MORE

To learn more about the EAR Program, visit 

https://highways.dot.gov/research/exploratoryadvanced-research. 

In the first 2 yr of the project, the researchers 

will host students for lab visits, give 

demonstrations and lectures about the project, 

and work with teachers to develop educational 

components for the classroom. In the third 

year, the researchers will offer internships for 

underrepresented female middle and high 

school students to learn about and contribute to 

the project. 

What Is the EAR Program?

The EAR Program supports longer term, 

higher risk research with the potential for 

transformative improvements to the U.S. 

transportation system. The EAR Program 

seeks to leverage promising expertise 

and advances in science and engineering 

to create breakthrough solutions to 

highway transportation issues.