Year: 2024
Type: conference-paper
Abstract: This study investigates a novel methodology for enhancing passenger comfort in highly automated vehicles (HAVs) by deriving driving patterns from professional chauffeurs. We collected detailed driving and interview data from chauffeurs, who are known for their smooth and comfortable driving styles. A Two-Step deceleration profile was derived from this data. Two different versions of the Two-Step Profile (V1 and V2), along with a One-Step profile, were integrated into an HAV and tested in various driving scenarios with 36 participants. Participants experienced each profile twice: once while attentive and once while engaged in a non-driving activity. By transferring the chauffeur's driving style to an HAV, this study evaluates the feasibility and comfort of human-like driving patterns in automated systems. The findings provide valuable insights for designing HAVs that prioritize passenger comfort, bridging the gap between human driving expertise and automated technology.
Authors: Stefanie Elisabeth Horn, Ruth Madigan, Michael Schulz, Andreas Schultz, Philipp Alt, Natasha Merat
Institutions: University of Leeds, Robert Bosch (Germany)
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W4402575884