CHALLENGES IN HOMOLOGATION PROCESS OF VEHICLES WITH ARTIFICIAL INTELLIGENCE
Máté Zöldy, Zsolt Szalay, Viktor Tihanyi
Abstract
The traditional automotive homologation processes aim to ensure the safety of vehicles on public roads. Autonomous Vehicles (AV) with Artificial Intelligence (AI) are difficult to account for in these conventional processes. This research aims to map and attempt to close the gaps in the areas of testing and approval of such automated and connected vehicles. During our research into the homologation process of traditional vehicles; functional safety issues, challenges of AI in safety critical systems, along with questions of cyber security were investigated. Our process focuses on the integration of the already existing functions and prototypes into new products safely. As a key result, we managed to identify the main gaps between Information and Communication Technology (ICT) and automotive technology: the rigidity of the automotive homologation process, functional safety, AI in safety critical areas and we propose a solution.