Datasets:

ClarusC64
/

autonomous-driving-driver-state-manifold-estimation-v0.1

id stringclasses 6 values	scene_context stringclasses 5 values	cabin_signal_summary stringclasses 6 values	gaze_summary stringclasses 6 values	grip_pressure_summary stringclasses 6 values	steering_micro_corrections stringclasses 6 values	blink_rate_summary stringclasses 4 values	posture_summary stringclasses 6 values	driver_state_label stringclasses 4 values	fatigue_score float64 0.12 0.82	distraction_score float64 0.1 0.79	agitation_score float64 0.08 0.84	confidence_estimate float64 0.69 0.8	state_transition_risk float64 0.18 0.7	notes stringclasses 6 values	constraints stringclasses 1 value	gold_checklist stringclasses 1 value
DSME-001	night highway; light traffic	long head nods; slow reactions	gaze forward 92%; long fixations	low steady grip	few corrections; delayed	blink rate high; closures long	slumped; minimal shifts	fatigued	0.82	0.18	0.12	0.76	0.68	Classic fatigue pattern	Under 220 words	label+fat+dis+agit+conf+risk
DSME-002	urban; dense traffic	phone glance bursts	gaze forward 61%; down-right glances	normal grip; intermittent release	corrections late; oscillation	blink normal	upright; frequent head turns	distracted	0.24	0.79	0.18	0.73	0.62	Distraction dominates	Under 220 words	label+fat+dis+agit+conf+risk
DSME-003	urban; dense traffic	jaw clench; rapid breathing	gaze forward 88%; scanning fast	high grip spikes	many micro corrections; sharp inputs	blink low	rigid; forward lean	agitated	0.2	0.22	0.84	0.74	0.7	Agitation shows in grip and input	Under 220 words	label+fat+dis+agit+conf+risk
DSME-004	suburban; moderate traffic	steady breathing	gaze forward 94%; mirror checks	moderate steady grip	smooth corrections	blink normal	neutral posture	baseline	0.12	0.1	0.08	0.8	0.18	Stable attentive driver	Under 220 words	label+fat+dis+agit+conf+risk
DSME-005	day highway; heavy traffic	yawning; slow head turns	gaze forward 84%; occasional drift	low grip; intermittent drop	few corrections; lane drift before correction	blink high	slight slump	fatigued	0.74	0.22	0.1	0.7	0.6	Fatigue with drift	Under 220 words	label+fat+dis+agit+conf+risk
DSME-006	urban; moderate traffic	conversation; frequent side looks	gaze forward 72%; left passenger glances	normal grip	corrections adequate	blink normal	turns toward passenger	distracted	0.18	0.67	0.12	0.69	0.46	Social distraction	Under 220 words	label+fat+dis+agit+conf+risk

What this dataset tests

Whether a system can infer driver state from cabin signals and driving context.

The output is a state manifold vector. Not a single label.

Required outputs

driver_state_label
fatigue_score
distraction_score
agitation_score
confidence_estimate
state_transition_risk

Scoring conventions

all scores range 0 to 1
labels are baseline, fatigued, distracted, agitated, mixed
transition risk flags likelihood of deterioration in the next window

Use case

Layer one of Driver-State and Vehicle-Response Coupling Manifold.

Supports:

human-in-the-loop safety
takeover risk estimation
adaptive policy selection based on driver state

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Size of downloaded dataset files:

2.68 kB

Size of the auto-converted Parquet files:

18.7 kB

Number of rows: