Analysis of Forecasting Techniques for the Growth of Vehicular Population in Nepal

Abstract

Forecasting of vehicular population is a critical process that entails predicting future values based on analyzing past trends and considering explanatory variables, such as economic and demographic factors. This becomes especially vital in the context of Nepal, where the accurate prediction of the future growth of the vehicular population is paramount for achieving sustainable transportation systems. This study employs three distinct forecasting methods: trend line analysis, econometric analysis, and time series analysis. These methods have been rigorously evaluated to assess their respective levels of accuracy in predicting Nepal's vehicular population. Notably, the results from time series analysis, particularly the ARIMA model, have demonstrated a remarkable level of precision compared to the traditional trend line and econometric analysis approaches. The superiority of the ARIMA model underscores its efficacy as the preferred method for accurate vehicular population forecasting, providing a reliable foundation for future planning and policy implementation. The forecasted figures for Nepal's vehicular population indicate anticipated counts of 8,914,793 for 2030 AD, 1,482,842,6 for 2040 AD, and 2,203,801,2 for 2050 AD. These predictions offer transportation planners invaluable insights for the effective implementation of new projects, ensuring that resources are optimally allocated and transportation sustainability is realized.