Help us understand how fatigue affects heavy vehicle drivers and operations across Australia. Select everything that resonates — there are no right or wrong answers.
~12 minutes
Fully confidential
Select all that apply
Section 1 of 10
SECTION 01
Background Information
Help us understand the industry context. All responses are confidential and reported in aggregate only.
What best describes your primary role?
Which industry segments are most relevant? Select all that apply
Long-haul interstate
Regional/rural
Metropolitan
Construction/civil
Mining/resources
Mixed operations
Fleet size?
Years of heavy vehicle industry experience?
States/territories of operation? Select all that apply
NSW
VIC
QLD
WA
SA
TAS
NT
ACT
National / multi-state
SECTION 02
Driver State & Behavioural Drift
These are subtle cognitive and emotional changes that often appear before fatigue is consciously recognised. Select all signals that are relevant in your experience.
Which early internal signals of fatigue have you observed or experienced in heavy vehicle drivers? Select all that apply
Increasing caffeine / stimulant use
"Zoning out" / autopilot driving
Reduced situational awareness
Irritability / emotional volatility
Micro-boredom → fidgeting / posture shifts
Reduced motivation to follow procedures
SECTION 03
Road Experience & Environmental Design
Fatigue as an emergent property of the road environment. Which of these factors contribute to driver fatigue?
Which road and environmental factors contribute meaningfully to driver fatigue? Select all that apply
Low visual variation / monotony exposure
Repetitive scenery (highways, desert)
High glare (sunrise/sunset angles)
Night driving / limited visual contrast
Road noise patterns (white noise effect)
Road surface vibration (too smooth/rough)
SECTION 04
Vehicle & Cabin Conditions
Often underestimated — cabin conditions are a major early fatigue amplifier. Which factors are significant?
Which vehicle and cabin conditions contribute to driver fatigue? Select all that apply
Cabin ergonomics / seat comfort
Noise levels (engine hum, road noise)
Suspension smoothness (overly smooth = sedating)
Dash reflections / windshield glare
Over-reliance on automation (cruise, lane assist)
Limited micro-adjustment options
SECTION 05
Workload, Scheduling & Operational Pressure
These shape fatigue risk before the shift even starts. Which pressures are most significant?
Which scheduling and operational factors drive driver fatigue risk? Select all that apply
Last-minute schedule changes
Tight delivery windows / unrealistic timelines
Lack of control over schedule
Administrative burden during shift
Multi-tasking (navigation, comms, etc.)
Time-of-day mismatch / circadian misalignment
SECTION 06
Psychosocial & Emotional Context
Often invisible in traditional fatigue models — these emotional and social factors matter enormously.
Which psychosocial factors contribute to driver fatigue? Select all that apply
Loneliness / isolation on long trips
Frustration with other drivers / road users
Conflict with supervisors or dispatch
Boredom from repetitive routes
Anxiety about targets or compliance
Social disconnection from family/community
SECTION 07
Health, Lifestyle & Recovery Quality
These determine a driver's baseline vulnerability to fatigue. Which factors are most significant?
Which health and lifestyle factors contribute to fatigue susceptibility? Select all that apply
Sleep quality (not just duration)
Diet (heavy meals, irregular eating)
Hydration levels
Exercise / physical activity levels
Alcohol or substance use
Caffeine timing and dependency cycles
Chronic health conditions
Mental health (stress, anxiety, depression)
SECTION 08
Journey Dynamics & Contextual Triggers
Fatigue isn't static — it fluctuates during the journey. Which dynamic factors are most relevant?
Which journey-specific factors affect fatigue levels during a shift? Select all that apply
Time into journey (early vs mid vs late)
Transition points (urban↔highway, highway→depot)
Post-break fatigue dips
Long uninterrupted driving periods
Rapid alertness decline from shift start
End-of-shift "push through" behaviour
Route familiarity (too familiar = complacency)
Unexpected disruptions (traffic, detours)
Seasonal factors (heat, daylight hours)
SECTION 09
Micro-Behavioural Coping Strategies
These are early adaptive (or maladaptive) responses to fatigue. Which strategies do drivers commonly use?
Which coping behaviours are most commonly used by drivers to manage fatigue? Select all that apply
Increasing caffeine intake
Opening windows / adjusting temperature
Music / podcasts to stay engaged
Changing posture frequently
Talking on phone to stay alert
Snacking for stimulation
Skipping breaks to "push through"
Over-reliance on automation
Self-talk ("just get through this leg")
Stretching / movement during stops
SECTION 10
AI Readiness & Technology Attitudes
How ready is the heavy vehicle industry to adopt AI-based fatigue management tools? Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree).
Share your perspective on AI in heavy vehicle fatigue management Open response
Rate your agreement with each statement 1 = Strongly Disagree → 5 = Strongly Agree
SECTION 10 of 10
Anything Else?
Final thoughts and recommendations from your experience.
Are there other fatigue predictors we haven't covered? Optional
What one thing would most improve fatigue management in the industry? Optional
Thank you for contributing
Your insights will directly shape the design of safer, smarter fatigue management tools for heavy vehicle drivers across Australia.
Responses are reported in aggregate only. No individual response is identifiable.
Research Dashboard
Heavy Vehicle Fatigue Survey — DRIVE S(AI)FE / NHVR