Back close

Lane Changing and Overtaking Decision Autonomous Vehicles

School: School of Engineering

Lane Changing and Overtaking Decision	 Autonomous Vehicles

In this project we introduce a modified deep auto encoder model based on extreme learning machine (ELM-MDAE) network to capture lane changing and overtaking behaviour of the vehicles and automatically extract the training data in real time. By using extracted data, LightCBM model is trained to establish a novel lane changing and overtaking decision model.

Related Projects

ClePa – A robot for cleaning staircase steps
ClePa – A robot for cleaning staircase steps
Amaran- A Robotic Coconut tree Climber
Amaran- A Robotic Coconut tree Climber
Smart Handheld Device for Detection of Gas Poisoning in Sewage Works
Smart Handheld Device for Detection of Gas Poisoning in Sewage Works
Fabrication of Silica Etch Mask using EBL and F Chemistry Dry Etching
Fabrication of Silica Etch Mask using EBL and F Chemistry Dry Etching
Automation of Transport and Building Feature Extraction using Deep Learning with Super-Resolution Enhancement of Satellite Imagery
Automation of Transport and Building Feature Extraction using Deep Learning with Super-Resolution Enhancement of Satellite Imagery
Admissions Apply Now