Navigation systems allow drivers to find the shortest or fastest path between two or multiple locations mostly using time or distance as input parameters. Various researchers extended traditional route planning approaches by taking into account the user's preferences, such as enjoying a coastal view or alpine landscapes during a drive. Current approaches mainly rely on volunteered geographic information (VGI), such as point of interest (POI) data from OpenStreetMap, or social media data, such as geotagged photos from Flickr, to generate scenic routes. While these approaches use proximity, distribution or other spatial relationships of the data sets, they do not take into account the actual view on specific route segments. In this paper, we propose Autobahn: a system for generating scenic routes using Google Street View images to classify route segments based on their visual characteristics enhancing the driving experience. We show that this vision-based approach can complement other approaches for scenic route planning and introduce a personalized scenic route by aligning the characteristics of the route to the preferences of the user.
['Nina Runge', 'Pavel Andreevich Samsonov', 'Donald Degraen', 'Johannes Schöning']
No more Autobahn!: Scenic Route Generation Using Googles Street View