This month’s guest article on driver fatigue comes from Dr Mike Lenné of Seeing Machines
Fatigue is not a driver problem – it’s a system problem
When fatigue is discussed in road safety, the advice is often simple: get more sleep. While well intentioned, this oversimplifies a complex issue. Fatigue is not solely the result of a poor night’s sleep, nor solely a driver responsibility. It is a predictable human factor shaped by biological, operational and organisational conditions, and managing it effectively requires a systems-based approach.
Fatigue is more complex than we think
Most people associate fatigue with feeling sleepy. In reality, it affects alertness, attention, reaction time, decision-making and overall performance. It can stem from insufficient or poor-quality sleep, disrupted patterns, extended wakefulness, heavy workloads, health factors and the body’s natural rhythms.
The consequences are significant. After 17 hours awake, reaction time and decision-making can decline to a level equivalent to a blood alcohol concentration of 0.05%. After 24 hours without sleep, impairment rises to levels that approximate a BAC of 0.10% (Dawson & Reid, 1997).
Fatigue also affects people differently. Two drivers may work the same shifts and comply with the same work and rest requirements, yet face different levels of risk depending on sleep history, health, age and individual circumstances. This is why fatigue cannot be managed reliably by hours worked alone.
The problem with self-assessment
A common assumption is that drivers will recognise when they are too fatigued to drive safely. Research suggests otherwise.
As fatigue develops, performance declines gradually, making it hard for people to judge how far alertness and decision-making have been affected. Drivers may know they are tired, but often underestimate when that tiredness has become a meaningful crash risk.
This creates a critical safety gap: drivers may believe they are functioning adequately even as performance deteriorates, reflecting a broader human limitation in self-assessing impairment (Van Dongen et al., 2003). Fatigue often develops quietly, without obvious thresholds or warning points.
Compliance does not equal safety
Compliance frameworks set minimum standards; they do not capture the full complexity of fatigue risk. A driver may be compliant yet still be operating with insufficient sleep or during periods of reduced alertness. A Working Time Society consensus position notes that prescriptive rule sets can ignore key biological factors, including the interaction between circadian and homeostatic processes, and that in around-the-clock operations, “the relationship between regulatory compliance and safety tends to break down” (Honn, Van Dongen & Dawson, 2019).
Circadian rhythms are central. Most people experience lower alertness in the early morning and, to a lesser extent, mid-afternoon. Sleep-related crashes show clear peaks at around 0200, 0600 and 1600, closely tracking these biological dips in alertness (Horne & Reyner, 1995).
A systems-based approach to fatigue management
Effective fatigue management requires organisations to look beyond individual responsibility and examine how operational design shapes risk, including scheduling, workload, organisational expectations and the culture around reporting fatigue. Drivers need to be able to say they are unfit to continue without fear of negative consequences.
Education matters, but information alone rarely changes outcomes. Drivers can make safe decisions only when systems support those decisions in practice.
Technology can support fatigue risk management. Driver Monitoring Systems (DMS), for example, can identify early signs of fatigue or reduced alertness in real time, adding another layer of insight alongside operational controls and driver self-awareness. The data generated by these systems can also provide organisations with greater visibility of how factors such as shift timing, scheduling, and operational demands influence fatigue risk across their fleet, enabling more informed safety decisions.
However, technology is most effective when integrated into a broader safety system that includes appropriate scheduling practices, a strong reporting culture, and leadership commitment to managing fatigue risk. Real-world fleet research supports this approach. One peer-reviewed study found that real-time in-cab fatigue alerts reduced verified fatigue events by approximately 66%, while combining in-cab alerts with real-time feedback to fleet managers achieved a 94% reduction (Fitzharris et al., 2017).
The aim is to continue to drive fatigue risk down through understanding and managing it proactively before it contributes to incidents.
Fatigue is a human factor, not a personal failing
The most important shift may be recognising that fatigue is not a lack of discipline or professionalism. It is a normal biological response to insufficient recovery and competing demands, affecting experienced and new drivers alike. No one is immune.
The organisations making the most progress are those that accept this reality and design systems that work with human capability rather than against it. Fleet safety depends on recognising the limits of human performance and building systems that help people operate safely within them.
For operators, the question is no longer whether fatigue is a risk – the evidence is unambiguous. The question is whether your organisation is managing it as a system or still treating it solely as a driver problem.
References
Dawson, D., & Reid, K. (1997). Fatigue, alcohol and performance impairment. Nature, 388(6639), 235-235.
Fitzharris, M., Liu, S., Stephens, A. N., & Lenné, M. G. (2017). The relative importance of real-time in-cab and external feedback in managing fatigue in real-world commercial transport operations. Traffic injury prevention, 18(sup1), S71-S78. https://doi.org/10.1080/15389588.2017.1306855
Honn, K.A., Van Dongen, H.P.A. & Dawson, D. (2019). Working Time Society consensus statements: Prescriptive rule sets and risk management-based approaches for the management of fatigue-related risk in working time arrangements. Industrial Health, 57(2), 264–280. https://doi.org/10.2486/indhealth.SW-8
Horne, J.A. & Reyner, L.A. (1995). Sleep related vehicle accidents. BMJ, 310(6979), 565–567. https://doi.org/10.1136/bmj.310.6979.565
Van Dongen, H.P.A., Maislin, G., Mullington, J.M. & Dinges, D.F. (2003). The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26(2), 117–126. https://doi.org/10.1093/sleep/26.2.117
