EXPLORING HUMAN-ERROR FACTORS CONTRIBUTING TO MOTORCYCLE ACCIDENTS IN HANOI CITY USING GREY RELATIONAL ANALYSIS

Abstract

Along with the development of the economy and society and the speedy increasing number of personal vehicles, especially motorcycles, many cities in developing countries like Hanoi (Vietnam) are facing many transportation problems, notably traffic accidents involving motorcyclists.  Motorcycle accidents are caused by main human-error factors, and could be considered as the typical grey system with the features of complexity and imperfect information. In this study, a grey relational analysis (GRA) model of the human-error factors is presented to quickly explore the main human-error factors contributing to traffic accidents caused by motorcycles. In this model, the grey relational degree and the grey relational order of each human-error factor also are determined to rank the main contributing human-error factors. Taking the data of road traffic accidents caused by motorcycles in Hanoi, the capital of Vietnam between 2015 and 2017 as experimental data, the grey relational degrees of human-error factors have been analyzed quantitatively through the GRA model. The experimental results show the first three human-error factors include wrong lane shifting, poor road observation, and speeding, respectively. The results also help to conduct effective countermeasures for controlling human errors and reducing road traffic accidents.