Design and Implementation of Smart Infrastructures and Connected Vehicles in A Mini-city Platform
Daniel Vargas, Ethan Haque, Matthew Carroll, Daniel Perez, Tyler Roman, Phong Nguyen, Golnaz Habibi
TL;DR
The work introduces a cost-effective, $1/10$-scale mini-city as a versatile test bed for autonomous and connected vehicles, bridging simulations and real-world urban complexity. It implements a smart intersection with V2I communication and deploys an ARC fleet to study perception, mapping, and depth estimation in occluded urban scenes. Key contributions include 2D ground-truth mapping with Gmapping, depth-estimation benchmarking among DPT, Depth Anything, and Marigold, and an ITS-focused evaluation of smart infrastructure improving intersection safety. The platform supports education and research in ITS by offering a reproducible, extensible environment for testing perception, navigation, and V2I strategies in urban-like scenarios.
Abstract
This paper presents a 1/10th scale mini-city platform used as a testing bed for evaluating autonomous and connected vehicles. Using the mini-city platform, we can evaluate different driving scenarios including human-driven and autonomous driving. We provide a unique, visual feature-rich environment for evaluating computer vision methods. The conducted experiments utilize onboard sensors mounted on a robotic platform we built, allowing them to navigate in a controlled real-world urban environment. The designed city is occupied by cars, stop signs, a variety of residential and business buildings, and complex intersections mimicking an urban area. Furthermore, We have designed an intelligent infrastructure at one of the intersections in the city which helps safer and more efficient navigation in the presence of multiple cars and pedestrians. We have used the mini-city platform for the analysis of three different applications: city mapping, depth estimation in challenging occluded environments, and smart infrastructure for connected vehicles. Our smart infrastructure is among the first to develop and evaluate Vehicle-to-Infrastructure (V2I) communication at intersections. The intersection-related result shows how inaccuracy in perception, including mapping and localization, can affect safety. The proposed mini-city platform can be considered as a baseline environment for developing research and education in intelligent transportation systems.