01520196

Component

The real-time OD prediction is a vital issue in DTA based traffic prediction systems. Previous researches along this direction are very sparse due to the low availability of OD volume observations. This study, utilizing the taxi GPS data collected in Singapore, demonstrated the effectiveness of different statistical models in predicting the future OD. The performance of four different classical statistical methods including historical average, ARIMA model, KNN method and ANN model are tested and compared using the dataset. The study has demonstrated that ANN models have highest overall prediction accuracy compared with other methods and can provide reliable prediction up to several hours range.

This paper was sponsored by TRB committee ADB30(4) Network Models in Practice. Alternate title: Empirical Study of Within-Day O-D Prediction Using Taxi GPS Data in Singapore.

01503729

14-5074

English

16p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures; References; Tables

Dynamic traffic assignment; Empirical methods; Global Positioning System; Mathematical prediction; Origin and destination; Real time information; Statistical analysis; Taxicabs; Traffic forecasting

Singapore

Highways; Operations and Traffic Management; I71: Traffic Theory

Transportation Research Board Annual Meeting 2014 Paper #14-5074

TRIS, TRB, ATRI

Jan 27 2014 3:46PM