Artificial Intelligent Systems and Machine Learning

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Artificial Intelligence Applications in Autonomous Cars:A Review


Affiliations
1 Savitribai Phule Pune University, Pune, Maharashtra CO-411041, India
2 Savitribai Phule Pune University, Pune, Maharashtra CO-411041, India
     

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The day by day increasing demand in automobile industry compel us to find more reliable and efficient ways of transportation. Self-driving autonomous vehicle will be the future in automobile industry. This review paper highlights on innovative technologies that can be used to develop autonomous vehicle. The backbone of driverless vehicle is the artificial intelligence. The path and distance detection is achieved with the help of image processing as well as real time embedded systems. LIDAR is used for visual odometry and perception of egomotion. Facial tracking, gaze tracking, gesture control is possible because of deep learning. GNSS has emerged as one of the prominent factors for the recent development in this area. Self-driving car eliminates human errors, increases road utility and traffic continuity which in turn results in reduction of traffic accidents.


Keywords

Intelligence, Deep Learning, Image Processing, LIDAR, Odometry.
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Abstract Views: 274

PDF Views: 2




  • Artificial Intelligence Applications in Autonomous Cars:A Review

Abstract Views: 274  |  PDF Views: 2

Authors

Anup Shete
Savitribai Phule Pune University, Pune, Maharashtra CO-411041, India
Manjusha Namewar
Savitribai Phule Pune University, Pune, Maharashtra CO-411041, India
Shreyash Agrawal
Savitribai Phule Pune University, Pune, Maharashtra CO-411041, India

Abstract


The day by day increasing demand in automobile industry compel us to find more reliable and efficient ways of transportation. Self-driving autonomous vehicle will be the future in automobile industry. This review paper highlights on innovative technologies that can be used to develop autonomous vehicle. The backbone of driverless vehicle is the artificial intelligence. The path and distance detection is achieved with the help of image processing as well as real time embedded systems. LIDAR is used for visual odometry and perception of egomotion. Facial tracking, gaze tracking, gesture control is possible because of deep learning. GNSS has emerged as one of the prominent factors for the recent development in this area. Self-driving car eliminates human errors, increases road utility and traffic continuity which in turn results in reduction of traffic accidents.


Keywords


Intelligence, Deep Learning, Image Processing, LIDAR, Odometry.

References