%0 Journal Article
%T Improving the Accuracy of Under-Fog Driving Assistance System
%A Bedine Kerim
%J Journal of Signal and Information Processing
%P 23-33
%@ 2159-4481
%D 2020
%I Scientific Research Publishing
%R 10.4236/jsip.2020.112002
%X Driving in fog condition is dangerous. Fog
causes poor visibility on roads leading to road traffic accident (RTA). RTA in
Albaha is common because of its rough terrain, in addition to the climate that
is mainly rainy and foggy. The rain season in Albaha region begins in October
to February characterized by rainfall and fog. Many studies have reported the
adverse effects of the rain on RTA which results in an increased rate of
crashes. On the other hand, Albaha region is not supported by a proper
intelligent transportation system and infrastructure. Thus, a Driver Assistance
System (DAS) that requires minimum infrastructure is needed. A DAS under fog
called No_Collision has been developed by a researcher in Albaha University.
This paper discusses an implementation of adaptive Kalman Filter by utilizing
Fuzzy logic system with the aim to improve the accuracy of position and
velocity prediction of the No_Collision system. The experiment results show a
promising adaptive system that reduces the error percentage of the prediction
up to 56.58%.
%K Driver Assistance System
%K GPS
%K Intelligent System
%K Kalman Filter
%K Fuzzy Logic
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=101784