BCIwiki (bciwiki.com) — Acceptance of wearable, non-invasive brain-computer interfaces (BCIs) for workload-adaptive driver assistance shifts systematically with the scenario, according to an online experiment with 1201 participants reported in Transportation Research Part F: Traffic Psychology and Behaviour on October 2, 2026. The authors are Theresa Wehrle, Lisa Sophia Krahnen, Günther Bauernfeind, Adrian Haar and Bertolt Meyer.
Driver monitoring systems improve traffic safety by detecting states such as drowsiness and cognitive overload. The authors note that future BCIs for driver monitoring and workload-adaptive automation could read neurophysiological signals directly and may be more sensitive than conventional systems. Whether drivers would accept them on real roads has gone largely unstudied.
The study used a between-participant vignette design. Each participant viewed 1 of 12 animated driving scenarios in which a BCI detected high workload and initiated assistance. The scenarios varied 3 characteristics: driver status (able-bodied or disabled), the assisted function (primary, secondary or tertiary driving task) and automation type (adaptive or hybrid). Respondents rated acceptance with an adapted version of the Unified Theory of Acceptance and Use of Technology (UTAUT2).
Acceptance was higher when the BCI supported driving-related functions and when the scenario showed a driver with a disability. The 2 activation modes tested produced no difference. The authors say the work brings sociotechnical factors into an established acceptance framework and can inform user-centered design of neuroadaptive driver assistance systems.