01557864

Component

Use of recent data is crucial for travel demand forecasting. There is a significant body of evidence that forecasts by models with recent data outperform those by models with older data. Even when the number of observations from the recent time point is significantly smaller than that from the older time point, utilising the former can result in better forecasts. However, forecasts made by a small number of observations are likely to be problematic where forecast performance is on average worse or is distributed with larger variance. Therefore, there must be a trade-off between data newness and number of observations. An opportunity exists to examine this trade-off in a context of commuting mode choice behaviours by utilising repeated cross-sectional data collected in Nagoya, Japan. Models are estimated utilising different number of observations (ranging from 50 to 10000) obtained from different time points (1971, 1981, and 1991), and they are applied to forecast commuting behaviours of 2001. Bootstrapping is adopted to have insights with statistical meaning. One of results is the following. Compared with models with larger number of observations (in the range of 550–10000 observations) from 1971, models using 1981 data with 300–500 observations and those using 1991 data with 200–250 observations produced statistically significantly better forecasts.

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

01550057

15-4178

English

15p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Commuters; Data quality; Mode choice; Statistical analysis; Traffic forecasting; Travel demand

Nagoya (Japan)

Data and Information Technology; Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-4178

TRIS, TRB, ATRI

Dec 30 2014 1:22PM