Page 206 - Special Topic Session (STS) - Volume 2

STS480 Firdaus A.A. et al.
1. Introduction
It is widely known that Advanced Driver Assistance System (ADAS) is
proven to significantly reduce the number of road accidents in general. A
recent study done by MIROS also establishes that driver behaviour of
passenger vehicles fitted with ADAS shows greater improvement than those
without the device, in terms of lower number of logged incidents. This paper
however will focus on commercial vehicles particularly for two different
groups; long-haul and short-haul drivers. There are arguments that long haul
drivers contribute more to road accidents numbers compared to short haul
drivers as discussed by Mishra, B., Sinha Mishra, N. D., Sukhla, S., & Sinha, A.
(2010) in their paper. According to Mishra et. al (2010), road accidents are
highly associated with the distance travelled. Similar argument was also
discussed by P.Philip, J.Taillard, C.Guilleminault, Salva Quera, M.A., B.Bioulac,
M.Ohayon (2019), where the finding draws a relation between long distance
travel and sleep-related accidents.
Road accidents may result from human factors, environment and/or
design of roads and vehicles factors. However, human factor often plays the
greatest role in causing road accidents, especially those involving commercial
vehicles (Abang Abdullah and Von, 2011). Human factor can be measured
using the driver score model which will help to determine risk profile of
drivers - whether the driver falls in the good score or a bad score band
according to their driving behaviour. It encompasses three predictive driving
behaviour parameters which contributes significantly to road crashes (based
on MIROS’s study). Research objective of this paper is to prove differences in
driver score between long haul driver and short haul driver group. Scope of
study for this analysis are three logistics companies based in Klang Valley
which trips covers both long haul and short haul travels across Peninsular
Malaysia.
The findings of this study will be significant in understanding the changes
in driver behaviour & associated risk factors due to the usage of ADAS in
commercial vehicle fleets. Relevant government authorities and regulators
may look at the prospect of implementing driver score as a new alternative to
measure driver’s risk of all categories and types of vehicles.

2. Methodology
This chapter discusses the analysis method used to derive driver score for
the two groups of drivers (long haul & short haul). For the purpose of this
study, independent t-test was used to ascertain the differences in driver score
means for the two groups of drivers. The source and background of the data
set will also be discussed in this section followed by the driver score
calculation.

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