Title: Short-term traffic flow forecasting using the autoregressive integrated moving average model in Metro Cebu (Philippines)
Authors: Dharyll Prince M. Abellana
Addresses: Department of Computer Science, University of the Philippines Cebu, Gorordo Ave., Lahug, Cebu City, 6000 Cebu, Philippines; Department of Industrial Engineering, Cebu Technological University, M.J. Cuenco Ave., Cebu City, 6000 Cebu, Philippines
Abstract: Traffic congestion is a major problem faced by many cities across the globe. The drawbacks of such problem are much more severe in developing countries due to the weak enforcement of policies, and lack of infrastructures to handle congestion, among others. In this paper, an autoregressive integrated moving average (ARIMA) model is developed to analyse the traffic flow dynamics of the Philippines, which is a relatively under-explored area in the current literature. Results show that the model attains good predictive performance. Several scholarly implications are drawn out from such results. Above all, the results provide theoretical lenses with which traffic conditions in developing countries can be examined. Moreover, such results aid in streamlining strategies and initiatives for managing traffic challenges in developing countries.
Keywords: short-term traffic forecasting; traffic in the Philippines; ARIMA; time series forecasting.
International Journal of Applied Decision Sciences, 2021 Vol.14 No.5, pp.565 - 587
Received: 20 Jan 2020
Accepted: 29 May 2020
Published online: 09 Jul 2021 *