Artificial Intelligence is basically the simulation of Human Intelligence processes by Machine, particularly Computers.
These processes will accept the learning through these rules to succeed in definite and self-correction such as acquisition of data and
rules for victimization of the information, reasoning. Explicit applications of Artificial Intelligence include skilled systems, speech
recognition and machine vision. Automation with inherent is progressively rising in various applications such as autonomous vehicles.
Drawing associate analogy from human social interaction, the conception of trust provides a legitimate foundation for describing the
connection between humans and automation. Main Purpose of Artificial Intelligence is to Implement Human Intelligence in Machines ?
Making systems that Perceive, Cogntive, Think, Learn, and Behave like Humans and to Create Expert Systems. Expert Systems that
exhibit intelligent behavior, learn, demonstrate, explain, and gives recommendations to its users. This paper is about implementation of
Autonomous Vehicles through Artificial Intelligence. This includes the Path Planning, Travel Patterns, and the ability of these vehicles
to assess their environments, which are treated as problems in inefficient autonomous vehicles. In addition, this paper includes the
evaluation of these problems. Path Planning involves selection of the optimal path for which the autonomous vehicle has to travel by
following a certain planning algorithm and the ability to sense the environment and obstacles in autonomous vehicles is also enhanced
through particular methods. Research methods that are addressed include Motion Planning to enhance the planning algorithm and also
Trajectory Planning to assess the uncertain environment in order to avoid certain obstacles for the automated vehicle to move in a safe
path. Hence, with the implementation of the following research methods Such as Voronoi diagrams and Evidential Occupancy Grid, we
were able to derive results for an Efficient Autonomous Vehicle.
Published In:IJCSN Journal Volume 8, Issue 4
Date of Publication : August 2019
Pages : 343-353
Figures :11
Tables : --
Pratyush Thota :
B.TECH-III Year-Computer Science and Engineering,GITAM UNIVERSITY
Rudraram, HYDERABAD,Telngana,India.
Bhargavaaditya Sivalenka :
B.TECH-III Year-Computer Science and Engineering,GITAM UNIVERSITY
Rudraram, HYDERABAD,Telngana,India.
K Radha :
Asst Profesor,Computer Science and Engineering ,GITAM UNIVERSITY
Rudraram, HYDERABAD,Telngana,India.
The automotive AI market reported that it's expected to be
valued at $783 million in 2017 and expected to succeed in
about to $11k million by 2025, at a CAGR of about 38.5%.
IHS Markit expected that the installation rate of AI-based
systems of latest vehicles would rise by 109% in 2025,
compared to the adoption rate of 8% in 2015.
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