01631686

Component

Understanding the changes in travel behavior over time in a transport system is essential to evaluate the performance and forecast the travel demand. However, long term travel behavior is difficult to observe and explain and even more difficult to forecast. This paper proposes an approach based on stochastic state equations to describe the gradual change of behavior over time by using panel data. Transition functions determine the likely change in behavior from one time period to another. To overcome the problem of a dynamic population and explain seasonal irregularities, the authors introduce “life cycle”, “potential demand” and “willingness to use” into their models. Then the authors discuss time-homogeneity issues and possibilities to identify states and calibrate the transition function. The model is applied to panel data from Kyoto University’s bicycle share system. The findings help us understand the adaption, “usage recover” and drop out behavior. Also the errors between actual and estimated values are analyzed to evaluate two model specifications. Overall, the results offer promising insights to a wide range of applications.

This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.

01618707

17-04112

English

19p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References; Tables

Bicycles; Campus transportation; Forecasting; Markov chains; Mathematical models; Stochastic processes; Travel behavior; Travel demand; Vehicle sharing

Kyoto University

Behavior change; Behavioral adaptation; Seasonal factors

Pedestrians and Bicyclists; Planning and Forecasting

Transportation Research Board Annual Meeting 2017 Paper #17-04112

TRIS, TRB, ATRI

Dec 8 2016 11:34AM