2023 Volume 79 Issue 22 Article ID: 22-22008
In this study, the authors aim to show an analysis method that can grasp the actual state of pedestrian behavior of tourist and congestion in the street space of a tourist destination using Wi-Fi packet sensor data and to clarify the impact of street usage on pedestrian behavior for different purposes. Through the analysis of the Higashiyama area in Kyoto, the authors demonstorate that: (1) Visualization of the number of hourly observation data by seasons was conducted to understand changes in the use of the link in response to measures for dispersion of tourists, such as lighting-up of famous signtseeing spots. (2) A mixed normal distribution assuming multiple purposes of tourists was estimated using a constrained EM algorithm, and the characteristic values of the distribution corresponding to simple movement, short-time stay, and longtime stay were determined. Furthermore, the time variation of the values was used to understand the tourist behavior and its situation in each link. (3) Based on the relationship between the number of observations and the mean value of each distribution for each purpose, the tourist behavior and environmental factors that affect travel time, as well as the level of congestion that suppresses purchasing behavior, were clarified.
