01506671

Component

In recent years, Artificial-Computational Intelligence (ACI) have found increasing applications in management of transportation infrastructures. Examples of ACI applications can be found in highway management however, compared to transportation planning, research of ACI methods applied to infrastructure management has been relatively limited. In this study was used artificial intelligence ANN (Artificial Neural Network). In particular the objective of the research study is to compare the predicted operating speed on tangents and circular curves for low-volume roads by using two different statistical approaches. The starting point was to predict the operating speed on investigated tangents and circular curves elements by using four regression equations developed using a traditional ordinary–least-squares method (OLS) as shown in a previous work of the authors. Then, the same database was used to calibrate new operating speed models by using ANN procedure. The results have shown that ANN models offer more reliable results in terms of predicted operating speed than those returned by OLS method on all circular curves and on tangents lengths greater than 500m. For tangents length less than 500 m, OLS method is to be preferred to ANN procedure.

This paper was sponsored by TRB committee AFB30 Low-Volume Roads. Alternate title: Modeling Low-Volume Road Operating Speed Using Artificial-Computational Intelligence.

01503729

14-0265

English

14p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures; References; Tables

Artificial intelligence; Least squares method; Low volume roads; Mathematical prediction; Neural networks; Operating speed

Highways; Operations and Traffic Management; Planning and Forecasting; I71: Traffic Theory

Transportation Research Board Annual Meeting 2014 Paper #14-0265

TRIS, TRB, ATRI

Jan 27 2014 2:11PM