Autonomous Vehicles

Course Name: 

Autonomous Vehicles (CS420)


B.Tech (CSE)




Programme Specific Electives (PSE)

Credits (L-T-P): 



Introduction to Autonomous Vehicles: Components, Architecture, Technologies, Operating Systems.
Localization: GNSS, LIDAR, Visual Odometry. Perception: Detection, Segmentation, Stereo, Optical flow, and
Scene flow, Tracking. Prediction & Routing: Planning and control, Traffic Prediction, Lane Level Routing.
Computer Vision Basics: Image formats, Edge detection, Convolution, Masking RoI, Corner detection,
Histograms, Feature extraction. Machine Learning: Linear and Logistic regression, SVMs and SVCs, Detecting
Cars using SVMs. Exercises using Deep Learning models and FPGAs: Line detection, Corner detection,
Vehicle speed determination, Traffic sign detection, Object recognition and tracking, Localization algorithm


Liu, et. al., Creating Autonomous Vehicles – Synthesis Lectures in Computer Science, Morgan Claypool – e1 - 2017, e2 – 2020
Michael E McGrath, Autonomous Vehicles: Opportunities, Strategies and Disruptions, 2e, Independent, 2019.
Hanky Sjafrie, Introduction to Self-Driving Vehicle Technology, Routledge (T&F), 2019
Ranjan & Senthamilarasu, Applied Deep Learning and Computer Vision for Self-Driving Cars, Packt Publishing; 1st edition, 2020.

Contact us

Dr. Manu Basavaraju
Head of the Department
Department of CSE, NITK, Surathkal
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.
Hot line: +91-0824-2474053
Email: hodcse[AT]nitk[DOT]ac[DOT]in


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