01152847

Component

A number of approaches including Neural Networks, time series, and traffic simulation modeling have been proposed for short-term travel time prediction. These approaches have achieved varying degrees of success in their abilities to predict travel time. Dynamic Neural Networks comprise a class of neural networks that is particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. This study compares the travel time prediction performance of three different Dynamic Neural Networks topologies with different memory setups. The results show that one Dynamic Neural Networks topology (the time-delay neural networks) out-performed the other two Dynamic Neural Networks topologies for the investigated prediction problem. This topology also performed slightly better than the simple multilayer perceptron neural networks that have been used in a number of previous studies for travel time prediction.

01147878

10-3105

English

15p

2010

Transportation Research Board 89th Annual Meeting

DVD

References; Tables (1)

Highway operations; Neural networks; Time series analysis; Topology; Traffic forecasting; Traffic simulation; Travel time

Travel Time Prediction System

Highways; Operations and Traffic Management; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2010 Paper #10-3105

TRIS, TRB

Jan 25 2010 11:31AM