Posted in | News | Automotive Robotics

New Framework to Model Traffic Information Systems in Connected Vehicle Systems

In the future, roads will probably carry autonomous vehicles that can communicate with each other through a system in which vehicles relay information—such as speed, destination, or impending lane change—and receive real-time feedback related to decisions such as changes in route essential to avoid traffic.

Image Credit: Surapol USanakul/

An intelligent connected vehicle system such as that could considerably enhance mobility and safety, as well as reduce congestion and emissions from vehicles idling in traffic. Meanwhile, it will also contribute to major complexity in already dynamic traffic patterns, which would make vehicle flow susceptible to instability.

The advent of connected vehicles will pose tremendous challenges to the robustness of the traffic management system. 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.

Sean X. He, Assistant Professor of Civil and Environmental Engineering, Rensselaer Polytechnic Institute

A grant from National Science Foundation Faculty Early Career Development (CAREER) will support He to create a theoretical framework for modeling traffic and information systems within a wider 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,” stated He.

Understanding the robustness of the overall system—a measure of how fast it can rebound following an event such as an influx of traffic, a crash, or interference in traffic management—forms the core of He’s research. The aim of the study is to eliminate huge fluctuations in the system that could result in instability or even collapse.

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

Sean X. He, Assistant Professor of Civil and Environmental Engineering, Rensselaer Polytechnic Institute

Modeling of this kind will offer information essential to other policymakers and researchers while developing future cyber and physical infrastructure and autonomous vehicle policies.

The model and derived tools will enable the development of robust traffic management procedures to realize the economic, social, and environmental advantages of connected vehicle 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. These real-time decisions could transform our current mobility policies, roadway designs, and traffic operations.

Sean X. He, Assistant Professor of Civil and Environmental Engineering, Rensselaer Polytechnic Institute

The study findings will be shared by He with his K-12 students, professionals, and the public with the help of simulation and virtual reality-based platforms.

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

Video Credit: School of Engineering, Rensselaer Polytechnic Institute.

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