Year: 2024
Type: conference-paper
Abstract: The automation of vehicles is progressing through several automation levels, with the goal of reaching full autonomy, i.e. level 5, which involves no steering wheel, brakes, pedals, or windshield. This is achieved by the vehicle taking on an increasing number of autonomous decision-making tasks under the guidance of smart control systems that are instilled with Artificial Intelligence (AI) and equipped with advanced sensor and actuator technologies. Major vehicle companies are competing to build the most talented driver, i.e. AI-agent. In this report, how the intelligence of Self-Driving Vehicles (SDVs) is being built by the automotive industry for the efficient deployment of handover wheels is analysed and applications of machine intelligence for SDVs are implemented through video capturing using Deep Learning (DL). The results show that i) the use of DL techniques as well as reinforcement learning (RL) – Deep RL approaches – can contribute to the intelligence of SDVs significantly and ii) SDVs, equipped with advanced mechatronics systems, can be fully autonomous with the level-5 automation as they are trained appropriately with proper datasets.
Authors: Jordon Lowe, Kaya Kuru
Institution: University of Lancashire
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403279546