结合旅游潜力图和景点静态特征的雨天旅游规划系统

Eriko Yamano, T. Takayama
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摘要

一般来说,对雨天旅行的支持在长时间内是必要的。阴雨天气对游客来说有很大的风险,会大大降低他们的旅行满意度。然而,它的解决方案还没有完全开发出来。在新冠肺炎疫情后的环境下,在实际领域支持旅游业可能再次成为当务之急。在本文中,我们假设“一个游客已经制定了一个晴天的旅行计划”。顺便说一下,存在一种社交方法:“移动旅游信息服务的潜在兴趣地图”。它在地图上按颜色和强度显示社交照片共享系统“Flickr”中的照片数量。本文对其进行了修正,以支持雨天出行计划。具体来说,我们在我们的系统中提出了以下三个菜单:1)每个降雨量程度显示“潜在兴趣地图”的菜单;2)根据其静态特征仅显示对下雨天气稳健的旅行地点的菜单;3)考虑到行为范围的减少,仅显示从基本点到指定距离范围内的旅行地点的菜单。通过这三个菜单,我们试图帮助游客在天气突然下雨的情况下有效地改变他/她的旅行计划。在实际中,我们通过以下两种方法对试点系统进行了评估:(1)对部分被试进行评估实验,(2)对旅游专业人士进行访谈。他们的结果都表明,我们的系统在支持游客在天气突然下雨时有效地改变他/她的旅行计划方面是有用的。
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Rainy Day Travel Planning System That Combines Tourism Potential Map with Static Characteristics of Spots
In general, support for rainy day travel is known to be imperative during long times. Rainy weather has significant risk for tourists to terribly reduce a satisfaction level of their travel. However, its solution is not fully developed. In Post-Covid-19 environment, support for tourism in an actual field could become imperative again. In the present paper, we put one assumption that “a tourist has already made his/her travel plan for a sunny day”. By the way, there exists a social approach: ‘potential-of-interest maps for mobile tourist information services’. It shows the amounts of the numbers of the photographs in social photograph sharing system ‘Flickr’ by color and intensity on a map. This paper modifies it for support of rainy day travel planning. Concretely, we propose the following three menus in our system: 1) a menu to show ‘potential-of-interest maps' per a degree of rainfall amount, 2) a menu to show only travel spot which is robust to rainy weather based on its static characteristics, and 3) a menu to show only travel spots within a specified distance range from a basic point, taking into account decrease of behavior range. With these three menus, we try to support a tourist to change his/her travel plan efficiently even if weather suddenly becomes rain. In actual, we have evaluated our pilot system by the following two method: (1) evaluation experiment with some subjects, and (2) interviews to tourism professionals. Both of their results shows that our system would be useful in order to support for a tourist to change his/her travel plan efficiently when weather has suddenly become rain.
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