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

Analysis of Seepage Induced Soil Mass Movements and Stabilization using sand Drains
Analysis of Seepage Induced Soil Mass Movements and Stabilization using sand Drains
Development of a Real-time, Process Control Method Based on Neural Network Model Using Feedback of Weld Pool Geometric Parameters Measured by a Vision-based Technique and Experimental Verification for Automated Arc Welding Processes
Development of a Real-time, Process Control Method Based on Neural Network Model Using Feedback of Weld Pool Geometric Parameters Measured by a Vision-based Technique and Experimental Verification for Automated Arc Welding Processes
Bio Water Filtration Unit for Improved Access to Clean Water – Communication for Sustainable Change
Bio Water Filtration Unit for Improved Access to Clean Water – Communication for Sustainable Change
Project Detection And Segmentation Of Repetitive Patterns In Images
Project Detection And Segmentation Of Repetitive Patterns In Images
ClePa – A robot for cleaning staircase steps
ClePa – A robot for cleaning staircase steps
Admissions Apply Now