Tourism Application Considering Waiting Time

Abstract

Currently, the proportion of independent travel is increasing in Japan. Therefore, earlier studies supporting itinerary planning have been presented. However, these studies have only insufficiently considered rural tourism. For example, tourist often use public transportation during trips in rural areas, although it is often difficult for a tourist to plan an itinerary for public transportation. Even if an itinerary can be planned, it will entail long waiting times at the station or bus stop. Nevertheless, earlier studies have only insufficiently considered these elements in itinerary planning. On the other hand, navigation is necessary in addition to itinerary creation. Particularly, recent navigation often considers dynamic information. During trips using public transportation, schedule changes are important dynamic information. For example, tourist arrive at bus stop earlier than planned. In such case, the waiting time will be longer than the waiting time included in the itinerary. In contrast, if a person is running behind schedule, a risk arises of missing bus. Nevertheless, earlier studies have only insufficiently considered these schedule changes. In this paper, we construct a tourism application that considers the waiting time to improve the tourism experience in rural areas. We define waiting time using static waiting time and dynamic waiting time. Static waiting time is waiting time that is included in the itinerary. Dynamic waiting time is the waiting time that is created by schedule changes during a trip. With this application, static waiting times is considered in the planning function. The dynamic waiting time is considered in the navigation function. To underscore the effectiveness of this application, experiments of the planning function and experiments of the navigation function is conducted in Tsuruoka City, Yamagata Prefecture. Based on the results, we confirmed that a tourist can readily plan a satisfactory itinerary using the planning function. Additionally, we confirmed that Navigation function can use waiting times effectively by suggesting additional tourist spots.