A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety - Nascimento, Alexandre Moreira; Vismari, Lucio Flavio; Molina, Caroline Bianca Santos Tancredi; Cugnasca, Paulo Sergio; Camargo, Joao Batista; Almeida, Jorge Rady de; Inam, Rafia; Fersman, Elena; Marquezini, Maria Valeria; Hata, Alberto Yukinobu (IEEE transactions on intelligent transportation systems, 2020)
Autonomous Vehicles (AV) are expected to bring considerable benefits to society, such as traffic optimization and accidents reduction. They rely heavily on advances in many Artificial Intelligence (AI) approaches and techniques. However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications. In this non-convergent context, this paper presents a systematic literature review to paint a clear picture of the state of the art of the literature in AI on AV safety. Based on an initial sample of 4870 retrieved papers, 59 studies were selected as the result of the selection criteria detailed in the paper. The shortlisted studies were then mapped into six categories to answer the proposed research questions. An AV system model was proposed and applied to orient the discussions about the SLR findings. As a main result, we have reinforced our preliminary observation about the necessity of considering a serious safety agenda for the future studies on AI-based AV systems.