In crowded inner-city regions it is often difficult to find a free parking space. Vehicles spend significant time searching for an available parking space near their intended destination and, as a result, city traffic grows. Studies conclude that, on average, around 30 percent of traffic in the investigated areas is parking search traffic. While often the city center is in the focus of these studies, many residential areas in cities also have a shortage of on-street parking spaces, forcing residents to circle around the blocks during evening hours until they find parking spaces within acceptable distance. Today, most drivers search for a parking search on their own, which can lead to inefficient search if drivers go through streets where another driver has already searched shortly before.
With new technologies available like vehicle-to-vehicle or vehicle-to-infrastructure communication, it may be possible for searching vehicles to share parking-related information in order to increase search efficiency. In this project, we therefore investigate whether communication and cooperation between drivers during parking search may help to reduce redundant searches in full street segments and thereby to effectively reduce average searching times and distances for all drivers.
This project is a joint cooperative work within the SocialCars Research Training Group, combining the expertise of most of the research disciplines involved in SocialCars. This collaboration enables us to approach the parking search problem through the different perspectives of transportation science, traffic psychology, decision-making in city logistics, information science and geo-informatics.