Study on User Behaviors in Urban Area with Ubiquitous Environment

在本研究中，我们将探讨泛在环境下的城市空间中的各种使用者行为模式。本文提出了几种城市商业区行人模型，用来描述在商业区中行走的行人。对于每一个行人，我们给出了一个场景来定义商店类别访问的顺序。在我们的模型中，城市购物区被划分为街区，并在每个商店类别中计算商店的大小。根据该场景，对于行人的每次访问，通过概率选择市区中的一个购物街区。概率是通过使用两个信息来计算的。一个是行人当前位置与街区之间的距离。另一个是街区内分类商店的规模。我们将我们的模型应用到城市地区的青森，山形和横滨市中心区，以评估参数，并拟合我们的模型，使用实际的行人数量和分类商店数据。结果表明，这些参数分别反映了青森市和山形市的行人特征。基于行人和用户行为模型，开发了一个模拟系统，用于模拟城市空间中的用户行为，特别是在购物区，包括商店、道路、铁路、火车站和交通信号灯。该仿真系统是为了分析我们无法处理分析模型的实际用户情况，如移动的用户的移动行为，步行行人在市中心的购物区之间走动的许多商店沿着道路，他们的团体到达和离开的铁路车站。我们观察流量和他们如何接受和接收数据包的变化与用户分布和讨论的接入点的位置策略。通过这个模拟系统，我们观察到几个接入点的位置模式在城市空间。

In this study, we deal with various user behavior model within urban space with ubiquitous environment. We propose several pedestrian model s in urban shopping area to describes pedestrians who walk up and down in the downtown shopping area. For each pedestrian, we give a scenario to defines shop categories to visit in order. In our model, the urban shopping area is divided into blocks and the sizes of shops are calculated at each shop categories. According to the scenario, for each visit of a pedestrian, one of the shopping block among the urban area is selected by a probability. The probability is calculated by using two information. One is the distance between the pedestrian's present location and the block. The other is the size of categorized shops included in the block. We applied our model to the urban area of Aomori, Yamagata and Downtown area in Yokohama to evaluate parameters and fit our model by using actual number of pedestrians and categorized shop data. As a result, we know that the parameters suggest the characteristics of Pedestrians in Aomori and Yamagata city respectively. Based on the pedestrian and user behavior models, we developed a simulation system to model user behavior in urban space, especially in shopping area, including shops, roads, railways, railway stations and traffic signals. This simulation system are made to analyze actual user situations which we can't deal analytical models, such as moving behavior of mobile users, walking pedestrians in downtown shopping area who walk around between many shops along roads, their group arrivals and departures by railways at stations. We observe traffic and how they accept and receive packets which changes with user distribution and discuss the access point location policy. By this simulation system, we observe several access points location patterns in a urban space.