Using Connected Intelligent Transportation to Enhance Vulnerable Road User Safety: Phase II Real-world Testing and Deployment

Principal Investigator(s):

Sikai Chen, Assistant Professor of Civil and Environmental Engineering – University of Wisconsin-Madison

Project Abstract:
As the development of Connected and Autonomous Vehicles (CAVs) becomes increasingly common on our roads, it is crucial to focus on the safety and equitable treatment of Vulnerable Road Users (VRUs). Building upon last year’s development of a human- in-the-loop digital twin system, this project enters Phase II, transitioning to real-world applications by developing a hardware-in-the-loop system for real-world testing and deployment. By utilizing the lab-developed CAV fleet and an array of edge computing devices, including 4D cameras and edge computers, coupled with data fusion algorithms, our objective is to refine, test, and deploy a framework that significantly enhances the interactions between CAVs and VRUs. Central to this initiative is the commitment to ensuring equitable access and safety for all road users, addressing the unique vulnerabilities of VRUs. This phase involves developing advanced data structures for efficient data management, deploying edge computing infrastructure for minimized response times, and creating custom algorithms for real-time data analysis. Executing real-world demonstrations on controllable test tracks, and potentially extending these tests to live urban environments such as Park Street, Madison, WI, will allow us to validate and exhibit the framework’s capacity for enhancing decision-making and ensuring both safety and equity in real traffic conditions.

Institution(s): University of Wisconsin-Madison

Award Year: 2024

Research Focus: Safety, Equity

Project Form(s):