Scenic route planning for tourists
- 6 October 2016
- journal article
- research article
- Published by Springer Science and Business Media LLC in Personal and Ubiquitous Computing
- Vol. 21 (1), 137-155
- https://doi.org/10.1007/s00779-016-0971-3
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 introduce Scenic 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.Keywords
This publication has 23 references indexed in Scilit:
- Scenic Athens: A personalized scenic route planner for touristsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Efficient Metaheuristics for the Mixed Team Orienteering Problem with Time WindowsAlgorithms, 2016
- The eCOMPASS multimodal tourist tour plannerExpert Systems with Applications, 2015
- On planning sightseeing tours with TripBuilderInformation Processing & Management, 2015
- A survey on algorithmic approaches for solving tourist trip design problemsJournal of Heuristics, 2014
- Mobile recommender systems in tourismJournal of Network and Computer Applications, 2014
- An iterative three-component heuristic for the team orienteering problem with time windowsEuropean Journal of Operational Research, 2014
- Electronic mobile guides: a surveyPersonal and Ubiquitous Computing, 2010
- The Generalized Maximum Coverage ProblemInformation Processing Letters, 2008
- Laid-Back Mobilities: Second-Home Holidays in Time and SpaceTourism Geographies, 2004