Scenic route planning for tourists. (February 2017) - Gavalas, Damianos; Kasapakis, Vlasios; Konstantopoulos, Charalampos; Pantziou, Grammati; Vathis, Nikolaos
Abstract Tourists visiting unknown destinations become increasingly dependent on mobile city guides to locate tourist services and retrieve informative content about nearby points of interest (POIs). Several mobile guides already support the provision of personalized tour recommendations to assist tourists in making feasible plans and visiting the most interesting POIs within their available time. However, existing tourist tour planners only regard available attractions as sites lacking physical dimensions (i.e., POIs are treated as 'points'). This restricts the modeling of POIs as attractions that may be entered/exited from a certain location (e.g., the main entrance). Although this is adequate for scheduling visits at museums, galleries, small squares or parks with single entry points, it fails to capture practical properties of typical tourist visiting styles in urban destinations. Tourists commonly appreciate strolling through pedestrian zones, market areas or urban areas of architectural, cultural and scenic value rather than only visiting sites of restricted access or taking the fastest route to move among city landmarks. Herein, we introduceScenic Athens, a context-aware mobile city guide for Athens (Greece) which provides personalized tour planning services to tourists. Far beyond than just providing navigational aid, Scenic Athens derives near-optimal sequencing of POIs along recommended tours, taking into account a multitude of travel restrictions and POI properties, so as to best utilize time available for sightseeing. Unlike similar tools, our application incorporates scenic (walking) routes (in addition to point POIs), thereby supporting more experiential exploration of tourist destinations. This broader perception of tourist attractions substantially increases the complexity of the entailed optimization problem's modeling. A user evaluation study validated the recommendation value, usability and perceived utility of the proposed application.