Open AccessFuture Traffic Prediction from Short Period Traffic Data
Author(s) -
I. Srinivasula Reddy,
Vikas Mendi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1006/1/012029
Subject(s) - regression analysis , computer science , transport engineering , linear regression , statistics , engineering , mathematics , machine learning
Prediction of future traffic is a complicated process which requires logical prediction methods and experience. The present study focused on the prediction of future traffic from the AADT data which is estimated from the one week continuous traffic data collected from the selected study area. State wise traffic contributions are estimated from the one-day number plate survey data and major states effecting the traffic in the study area are observed. The population data, vehicle registration data and economic data of the major states which are observed through number plate survey are used for the prediction of future traffic data. The vehicle growth rates were calculated using average vehicle registration growth rate method and nonlinear regression (power regression). Finally, the growth rates were decided according to the traffic design norms provided by NHAI. The year wise future traffic was predicted and presented in this paper from the year 2013 to 2040. The changes in Level of Service (LOS) of the NH 8A for four lane and six lane configuration is detailed for the future scenario.