Forecasting Road Traffic Deaths in Thailand: Applications of Time-Series, Curve Estimation, Multiple Linear Regression, and Path Analysis Models

Sajjakaj Jomnonkwao, Savalee Uttra and Vatanavongs Ratanavaraha
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Sajjakaj Jomnonkwao: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand
Savalee Uttra: Department of Logistics Engineering and Transportation Technology, Faculty of Engineering and Industrial Technology, Kalasin University 62/1 Kaset Sombun Road, Kalasin Subdistrict, Mueang District, Kalasin 46000, Thailand
Vatanavongs Ratanavaraha: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-District, Muang District, Nakhon Ratchasima 30000, Thailand

Sustainability, 2020, vol. 12, issue 1, 1-17

Abstract: In 2018, 19,931 people were killed in road accidents in Thailand. Thus, reduction in the number of accidents is urgently required. To provide a master plan for reducing the number of accidents, future forecast data are required. Thus, we aimed to identify the appropriate forecasting method. We considered four methods in this study: Time-series analysis, curve estimation, regression analysis, and path analysis. The data used in the analysis included death rate per 100,000 population, gross domestic product (GDP), the number of registered vehicles (motorcycles, cars, and trucks), and energy consumption of the transportation sector. The results show that the best three models, based on the mean absolute percentage error (MAPE), are the multiple linear regression model 3, time-series with exponential smoothing, and path analysis, with MAPE values of 6.4%, 8.1%, and 8.4%, respectively.

Keywords: accident forecasting; multiple linear regression model; time-series; path analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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