Abstract—The ability to predict the behavior of cars that are parked in an urban area can be very useful to the development of vehicular networks that leverage these parked cars. In this paper, we analyze the mobility patterns of people living in US cities who use cars as their primary means of transportation. We process and analyze survey data from the metropolitan areas of Atlanta, Chicago, and Knoxville, to extract statistics on the parking behaviors of individual cars.
We accompany our study with a synopsis of how parked cars are being leveraged in urban vehicular networks, and show possible use cases for fine-grained parking models. We then provide daily and hourly analytical models of parking events, along with useful derivations of key parking statistics.
The data we present in this study conclusively shows that parking events can be classified into two major, clearly-identifiable groups according to the time cars spend parked; that each group is modeled by distinct distributions of probability; that these patterns vary substantially throughout the day and, therefore, are better modeled through time-evolving processes; and finally, that these trends are very similar among different cities.