Publication: Study of Road Accident Prediction Model by Using Pls-Sem
Date
2020-09
Authors
Nur Fadilah binti Adriyanshah
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Abstract
Many developed countries in line with the increase in road transport, and consequently
an increase in the rate of accidents, are searching for effective ways to reduce road
accidents including Malaysia. In the area of traffic safety, in order to identify factors
contributing to accidents, conventional methods which generally based on regression
analysis are used. However, these methods only detect accidents in different roads, but
cannot clearly identify the cause of accidents and define the relationship between them.
In addition, the methods used have two major limitations: 1- Postulate the structure of
the model, and, 2- Observability of all variables. Due to the limitations discussed and
also due to the complex nature of human factors, and the impact of road conditions,
vehicle and environment on human factors, the aim of this study is to provide a useful
tool for defining and measuring road, traffic and human factors, to evaluate the effect
of each of them in accidents which caused by carelessness, directly and indirectly by
using structural equation modeling with the partial least squares approach. Compared
with the regression-based techniques or methods of pattern recognition that only a layer
of relationships between independent and dependent variables is determined, the SEM
approach provides the possibility of modeling the relationships between multiple
independent and dependent structures. Moreover, the ability to use unobservable hidden
variables, by using observable variables would be possible. This study also explained
briefly current trends at FT050 base on traffic engineering observation and succeed to
identify and rank factors influencing road accident at FT050. Data used for this
modelling are based on three main data which are questionnaire data for human
behaviour factor , traffic study data where onsite investigation has been done and lastly
accident data taken from Ministry of Works Malaysia for road and surrounding factor.
Description
Interim Semester 2020/2021
Keywords
Rate of Accidents