Year: 2024
Type: conference-paper
Abstract: This paper addresses the problem of human-based driver support. Nowadays, driver support systems help users to operate safely in many driving situations. Nevertheless, these systems do not fully use the rich information that is available from sensing the human driver. In this paper, we therefore present a human-based risk model that uses driver information for improved driver support. In contrast to state of the art, our proposed risk model combines a) the current driver perception based on driver errors, such as the driver overlooking another vehicle (i.e., notice error), and b) driver personalization, such as the driver being defensive or confident. In extensive simulations of multiple interactive driving scenarios, we show that our novel human-based risk model achieves earlier warning times and reduced warning errors compared to a baseline risk model.
Authors: Tim Puphal, Benedict Flade, Matti Krüger, Ryohei Hirano, Akihito Kimata
Institution: Honda (Germany)
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4408793858