Abstract
To discuss or evaluate certain policies for a smart city (e.g., urban transportation systems), it is effective to develop an agent-based simulation that can reproduce an individual's travel behavior and social interaction. Here, activity-travel data is needed to develop a behavior model. However, it is difficult to collect such data over a long time period due to a heavy burden on subjects of the survey. This study proposes a web system to collect an individual's schedule data easily from travel information. Our proposed system has two key characteristics: 1) travel information (e.g., which route is best at a particular time) is recommended automatically based on the concept of a prism when the user enters a new schedule, 2) researchers can utilize users' schedule information as activity-travel data without conducting a special survey. We tested the system with students as users, who expressed satisfaction with the system's usability as well as operability.
