Rise of Connected Autonomous Vehicles Will Require New Models for Managing Traffic

NSF CAREER grant supports Rensselaer modeling of complex connected vehicle systems

Future roads will likely carry autonomous vehicles that communicate with one another in a system where vehicles relay information — like destination, speed, or upcoming lane change — and then receive real-time feedback about decisions like route changes necessary to avoid traffic.

Such an intelligent connected vehicle system could vastly improve mobility and safety, while reducing congestion and emissions from vehicles idling in traffic, but it will also add significant complexity to already dynamic traffic patterns, making vehicle flow vulnerable to instability.

“The advent of connected vehicles will pose tremendous challenges to the robustness of the traffic management system,” said Sean X. He, an assistant professor of civil and environmental engineering at Rensselaer Polytechnic Institute. “We have nice dynamic modeling of our current traffic system; however, if we add another layer — that’s the communication layer — it becomes very chaotic. We don’t yet know how to formulate the complex interactions that would occur between the traffic and communication layers.”

With the support of a National Science Foundation Faculty Early Career Development (CAREER) grant, He will develop a theoretical framework to model traffic and information systems within a broader connected vehicle system.

“What I’m interested in is: How we can model it as a system? We want to understand the interactions between vehicles and interactions between vehicles and infrastructures,” He said.

At the core of this research is an understanding of the robustness of the overall system — a measure of how quickly it can rebound after an event like a crash, an influx of traffic, or interference in traffic management. The goal is to prevent large fluctuations within the system that could lead to instability or even collapse.

“We want to know: Where are the critical points?” He said. “If something is going to happen, how can we predict it before the system collapses?”

This type of modeling will provide necessary information to other researchers and policymakers as future cyber and physical infrastructure is built and as autonomous vehicle policies are developed. The model and derived tools will facilitate the design of robust traffic management procedures to bring about social, economic, and environmental benefits of connected vehicles systems.

“Connected vehicle systems can allow vehicles and infrastructure to share information and allow all roadway users to make real-time decisions in a distributed fashion,” He said. “These real-time decisions could transform our current mobility policies, roadway designs, and traffic operations.”

He will share his findings with K-12 students, professionals, and the public using simulation and virtual reality-based platforms.