Transfer Learning and Organic Computing for Autonomous Vehicles
It addresses the problem of handling unseen challenging situations for autonomous vehicles, but it is incremental as it reviews existing methods without introducing new ones.
The paper explores how transfer learning, online transfer learning, and organic computing can be applied to autonomous vehicles to convert new experiences into knowledge for better future preparedness, but it does not report specific results or concrete numbers.
Autonomous Vehicles(AV) are one of the brightest promises of the future which would help cut down fatalities and improve travel time while working in harmony. Autonomous vehicles will face with challenging situations and experiences not seen before. These experiences should be converted to knowledge and help the vehicle prepare better in the future. Online Transfer Learning will help transferring prior knowledge to a new task and also keep the knowledge updated as the task evolves. This paper presents the different methods of transfer learning, online transfer learning and organic computing that could be adapted to the domain of autonomous vehicles.