Abstracting routes to their route-defining locations

Today's navigation assistance systems provide turn-by-turn instructions, which only focus on the next decision to take without offering any larger context. Information presentation is uniform and disconnected, i.e., local instruction equally important not linked other decisions or overall route This differs from how people usually give instructions hinders spatial learning. In order (re-)establish this context, we present an approach identifying those locations along a that define its characteristics, termed route-defining locations. These are prominent, easily recognized locations, help relating environment's structure navigator's existing knowledge about environment. The allows for determining different levels of detail. Thus, at same time it offers mechanism simplifying (or abstracting) route. paper, particularly latter aspect, presenting in detail For given route, we, first, simplify shape extract turns characterize shape. Then, rank landmarks streets based their prominence. Finally, include simplified correspond most prominent streets. result set extracted shape, agent-based simulation, then evaluate approach's ability abstract defining Results show that, indeed, our effective respect, but success depends ‘matching’ abstraction agent's