On the road with self-driving assistance
the future of the automotive sector. This may
incur substantial cost in developing appropriate
infrastructures to cater to the AV environment [4].
Apart from that, another aspect on mixed
traffic composition and road user behaviour in
this region, such as high motorcycle volume and
motorcyclists’ risk-taking behaviour in terms
of lane splitting and weaving, should also be
taken into consideration. Thus, the development
of artificial intelligence (AI) for AVs should not
only consider the traffic situation in developed
countries, but also cover the more complicated
traffic situation in developing countries such as
Malaysia.
In addition, to realize the AV initiative in
Malaysia, a readiness plan on Vehicle Type
Approval (VTA), licensing system and insurance
coverage should be developed and harmonized
with the existing legal framework. Elements
on vehicle and system security as well as data
privacy (location and destination tracking) should
also be in the pipeline to ensure comprehensive
implementation of AV.
Nevertheless, it is necessary to improve
current technologies that assist drivers (in this
case, SAE level 1) to ensure the systems’ reliability
and subsequently pave the way to self-driving
vehicles.
REFERENCE
[1] Golias J, Yannis G, Antoniou C. Classification of
driver-assistance systems according to their
impact on road safety and traffic efficiency.
Transport Reviews. 2002 Jan;22(2):179–96.
[2] SAE International. SAE J3016 - Taxonomy and
definitions for terms related to on-road motor
vehicle automated driving systems. SAE
International; 2014.
[3] Visvikis C, Smith TL, Pitcher M, Smith R.
Study on lane departure warning and lane
change assistant systems. Wokingham, UK:
Transport Research Laboratory (TRL); 2008.
Report No.: PPR 374.
[4] Bagloee SA, Tavana M, Asadi M, Oliver
T. Autonomous vehicles: challenges,
opportunities, and future implications for
transportation policies. Journal of Modern
Transportation. 2016 Dec 1;24(4):284–303.
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