Abstract
This study proposed a context-aware ontology-based route finding algorithm for self-driving tourists. In this algorithm, two ontologies—namely drivers’ experiences and required tourist services—were used according to tourist requirements. Trips were classified into business and touristic. The algorithm was then compared with Google Maps in terms of travel time and travel length for evaluation. The results showed that the proposed algorithm performed similarly to Google Maps in some cases of business trips and better in other cases, with a maximum 10-min travel time difference. In touristic trips, the capabilities of the proposed algorithm were far better than those of Google Maps.
Highlights
Various tours are organized worldwide for travelling to different countries, offering a general travel plan for tourists and neglecting individuals’ interests
Two routes may be requested by tourists: a business trip which is from a source and destination and a touristic trip to visit tourist destinations on the way
If a business trip is requested by the tourist, the driver’s experience ontology and route finding algorithm are only used but in the case of a touristic trip, both ontologies are used
Summary
Various tours are organized worldwide for travelling to different countries, offering a general travel plan for tourists and neglecting individuals’ interests. The number of tourists interested in independent travel and personalized plans have been on the rise. Most such tourists are interested in self-driving and sightseeing in destination cities by renting cars. In [1], the authors offered a mobile agent, known as the Dynamic Tour Guide (DTG), which plans travel according to the user’s requirements. This application mainly focuses more on navigation within tourist destinations but less on moving from one tourist destination to another
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