Improving Egovehicle Control in Deep Learning training Pipeline for Autonomous Cars

This is Syamimi’s MSc work. We continue our exploration in self-driving car technology.

Vehicles Adaptability in Deep Learning training Pipeline for Autonomous Cars

Autonomous driving deep-learning models are trained on a dataset from a particular egocar. We hypothesize the performance will deteriorate when used on a different egocar. In this project, we study suitable imitation learning pipelines for autonomous car that will improve its performance when deployed on different egocars.




  • Noorsyamimi Abdur Ajak, Wee Hong Ong and Owais Ahmed Malik, “A Comparison of Imitation Learning Pipelines for Autonomous Driving on the Effect of Change in Ego-vehicle,” 35th IEEE Intelligent Vehicles Symposium (IV), Jeju, South Korea, 2-5 June 2024 (paper, poster)


Video segments showing performance of the models deployed on different ego-vehicles.