Vehicle Automation & ADAS

Research on how people drive, supervise, ride in, and respond to automated and driver-assistance systems, plus those systems' outward signals.

What's here. Empirical and modeling work on drivers and passengers with automation engaged: takeover transitions, mode awareness, automation surprise, trust calibration, hands on hands off engagement, adas effectiveness, and passenger motion sickness comfort. The outward and networked side sits here too, including ehmi external hmi, odd communication, v2x connected vehicle, and teleoperation remote driving, along with acceptance adoption. Also the automation-specific trust and complacency constructs — trust in automation foundations and automation complacency bias — re-parented here 2026-08-11 because their strongest neighbours are all topics in this category.

What isn't here.

• camera-based drowsiness and distraction detection algorithms, dms validation, and dms regulation — Driver State Monitoring (DMS). Driver monitoring ships as an ADAS feature, so readers expect it here. The sensing stack that watches the driver is shelved separately; this category covers how drivers behave with automation on, not how a system infers their state.
• situational awareness and attention allocation measurement — Cognitive Workload. mode awareness here is narrow: whether the driver knows which automation state is active and what it is doing. Work on measuring situational awareness and attention, including in automated vehicles, is in cognitive workload.
• situation awareness theory and human error taxonomies as cross-domain constructs — General Human Factors (Cross-Domain). The general-theory layer stated at the operator level, applicable beyond driving. Trust and complacency as they apply to driving automation are here, not there.