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TIME SERIES MODELING FOR FORECASTING TRAFFIC GROWTH RATE
| 题名： | TIME SERIES MODELING FOR FORECASTING TRAFFIC GROWTH RATE |
| 正文语种： | eng |
| 作者： | SHABANA THABASSUM;KUMAR M |
| 作者单位： | Department of Civil Engineering Osmania University Hyderabad Telangana;Department of Civil Engineering Osmania University Hyderabad Telangana |
| 摘要： | Road transportation is the principal mode of transport in India. To offer an improved Level of Service (LOS) along the National Highways (NH) and to enhance their capacity, it is required to project the traffic exactly in the long-term duration. The objective of this study is to calculate traffic growth rates for the National highways taking up the case of National highways passing through Uttar Pradesh state and carrying majority of the traffic from the same state in different approaches and to suggest the best model for future traffic projections. Four different approaches like growth rate based on past vehicle registration, Transport demand elasticity approach, Single Exponential Smoothing approach and Auto Regressive Integrated Moving Average Technique (ARIMA) have been examined in time series modeling for the establishment of traffic growth rates. It is established that, the growth rates obtained from past vehicle registration data are much on the higher side. Almost the same scenario is shown by econometric modeling procedures. For all the modes of road transport, the growth rate obtained from the Single Exponential Smoothing technique is much on the lower side. Growth rates obtained from ARIMA model is considered satisfactory as it shows almost average values of the remaining three methods. Hence ARIMA models are suggested to be the best models for future traffic growth rate calculation and traffic projections. |
| 出版年： | 2021 |
| 期刊名称： | Indian Highways |
| 卷： | 49 |
| 期： | 8 |
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