| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥330,000)
Fiscal Year 2007: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2006: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Research Abstract |
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.
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