# A Physical Testbed for Intelligent Transportation Systems

## TL;DR

This paper introduces a comprehensive hardware-software testbed for intelligent transportation systems, enabling more realistic development and testing of traffic management algorithms beyond traditional simulations.

## Contribution

It presents a detailed design of a physical testbed integrating connected vehicles, intersection controllers, and data analytics for ITS research and development.

## Key findings

- Initial results demonstrate improved control algorithm performance.
- The testbed offers higher fidelity than simulations.
- Framework supports development of advanced traffic management solutions.

## Abstract

Intelligent transportation systems (ITSs) and other smart-city technologies are increasingly advancing in capability and complexity. While simulation environments continue to improve, their fidelity and ease of use can quickly degrade as newer systems become increasingly complex. To remedy this, we propose a hardware- and software-based traffic management system testbed as part of a larger smart-city testbed. It comprises a network of connected vehicles, a network of intersection controllers, a variety of control services, and data analytics services. The main goal of our testbed is to provide researchers and students with the means to develop novel traffic and vehicle control algorithms with higher fidelity than what can be achieved with simulation alone. Specifically, we are using the testbed to develop an integrated management system that combines model-based control and data analytics to improve the system performance over time. In this paper, we give a detailed description of each component within the testbed and discuss its current developmental state. Additionally, we present initial results and propose future work. Index Terms: Smart city, Intelligent transportation systems, Human-in-the-loop, Data analytics, Data visualization, Traffic network management and control, Machine learning.