  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.
