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

Influence of particle irradiation on photo-absorption and charge separation kinetics in Organic Solar Cells
Influence of particle irradiation on photo-absorption and charge separation kinetics in Organic Solar Cells
Hand Orthotic Device
Hand Orthotic Device
Driving Assistance System Based Ongaze Tracking and Road Scene Events Detection
Driving Assistance System Based Ongaze Tracking and Road Scene Events Detection
Analysis and Evaluation of Multilayer Shear Damped Viscoelastic Treatments for Launch Vehicle Applications
Analysis and Evaluation of Multilayer Shear Damped Viscoelastic Treatments for Launch Vehicle Applications
A Framework for event modeling and detection for Smart Buildings using Vision Systems
A Framework for event modeling and detection for Smart Buildings using Vision Systems
Admissions Apply Now